CN116859788A - Multi-equipment task scheduling central control management platform - Google Patents
Multi-equipment task scheduling central control management platform Download PDFInfo
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- 239000000523 sample Substances 0.000 claims abstract description 214
- 238000010257 thawing Methods 0.000 claims abstract description 46
- 239000012472 biological sample Substances 0.000 claims abstract description 30
- 238000011144 upstream manufacturing Methods 0.000 claims abstract description 21
- 230000005540 biological transmission Effects 0.000 claims abstract description 12
- 230000000977 initiatory effect Effects 0.000 claims abstract description 10
- 238000002474 experimental method Methods 0.000 claims description 22
- 238000012163 sequencing technique Methods 0.000 claims description 9
- 238000000034 method Methods 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
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- 238000004989 laser desorption mass spectroscopy Methods 0.000 description 4
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- 239000006101 laboratory sample Substances 0.000 description 1
- 238000003032 molecular docking Methods 0.000 description 1
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Abstract
The invention provides a multi-equipment task scheduling central control management platform, which comprises the following components: the transmission module is used for receiving the target order from the upstream system and transmitting the target order to the central control system; the sample determining module is used for initiating a notification instruction to the intelligent biological sample library according to the target order based on the central control system, and selecting a target sample from the intelligent biological sample library based on the notification instruction; the scheduling module is used for scheduling the intelligent robot, carrying the target sample to the thawing frame based on the intelligent robot, controlling the intelligent robot to carry the target sample to the experimental equipment based on the central control system after thawing the target sample, automatically transmitting and executing data among a plurality of target equipment when the target sample is tested, returning the target sample to the warehouse based on the central control system after the test is completed, and returning the test result to the central control system. The use efficiency of equipment is improved, the cost is reduced, the manual intervention is greatly reduced, and the intelligent production is realized in a help laboratory.
Description
Technical Field
The invention relates to the technical field of intelligent control, in particular to a multi-equipment task scheduling central control management platform.
Background
At present, when laboratory samples are subjected to detection service, the dispatching of a plurality of devices is generally involved, and the laboratory biological samples are subjected to experimental operation by matching the dispatching of the plurality of devices, so that normal production experiments of a laboratory are ensured;
however, in the prior art, the robot is often controlled manually to realize the taking of the biological sample, only semi-intelligent is realized, the production efficiency of a laboratory is reduced through manual control, the detection tasks are piled up, and further the cost is increased, so that the laboratory is not beneficial to experimental production;
therefore, in order to overcome the technology, the invention provides a multi-device task scheduling central control management platform.
Disclosure of Invention
The invention provides a multi-equipment task scheduling central control management platform which is used for receiving a target order through an upstream system, so that the target order is read and analyzed in a central control system, a target sample is accurately locked in an intelligent biological sample library, the target sample is conveyed to a thawing rack through an intelligent dispatching robot, then the thawing rack is conveyed to experimental equipment for experiments, and the target sample is returned to the library after the experiments are finished, and the tasks are reasonably scheduled for processing, so that the accumulation of detection tasks can be effectively reduced, the use efficiency of the equipment is improved, and the cost is reduced; the LIMS central control management platform is connected with the upstream ordering system, the intelligent biological sample library, the intelligent robot and the inspection equipment, so that manual intervention is greatly reduced, and the intelligent production is realized in a laboratory.
The invention provides a multi-equipment task scheduling central control management platform, which comprises the following components:
the transmission module is used for receiving the target order from the upstream system and transmitting the target order to the central control system;
the sample determining module is used for initiating a notification instruction to the intelligent biological sample library according to the target order based on the central control system, and selecting a target sample from the intelligent biological sample library based on the notification instruction;
the scheduling module is used for scheduling the intelligent robot, carrying the target sample to the thawing rack based on the intelligent robot, and controlling the intelligent robot to carry the target sample to the experimental equipment based on the central control system after thawing the target sample, wherein the experimental equipment comprises a plurality of pieces of equipment, and data among the plurality of pieces of equipment are automatically transferred and executed when the target sample is subjected to experiments, so that the transfer of the target sample among the plurality of pieces of experimental equipment is completed;
meanwhile, after the experiment is completed, the robot is controlled to restore the target sample based on the central control system, and the experimental result is returned to the central control system.
Preferably, a multi-device task scheduling central control management platform, a scheduling module, further includes:
the parameter recording unit is used for automatically recording experimental parameters based on experimental equipment and placing the experimental parameters into a target folder when the intelligent robot carries the target sample to the experimental equipment;
and the analysis unit is used for analyzing the target folder based on the central control system to generate an experimental result when the experimental equipment completes the experiment on the target sample, and returning the experimental result to the upstream system.
Preferably, a multi-device task scheduling central control management platform, a transmission module, includes:
the order generation unit is used for reading the client requirements and generating a target order according to the client requirements;
an order receiving unit for receiving a target order based on an upstream system;
and the order transmission unit is used for transmitting the target order to the central control system based on the upstream system after the target order is received.
Preferably, a multi-device task scheduling central control management platform, a sample determining module, includes:
the order reading unit is used for reading the target order based on the central control system and determining sample keywords and sample calling logic keywords in the target order;
the instruction generation unit is used for generating a first instruction element based on the sample keyword, generating a second instruction element based on the logic keyword, acquiring the association relation between the sample keyword and the sample calling logic keyword, and fusing the first instruction element and the second instruction element based on the association relation to generate a notification instruction;
the instruction initiating unit is used for initiating a notification instruction to the intelligent biological sample library;
a target sample calling unit, configured to:
determining a target sample and a retrieval sequence of the target sample according to the notification instruction based on the intelligent sample library;
and orderly calling the target samples in the intelligent sample library based on the calling sequence of the target samples.
Preferably, a multi-device task scheduling central control management platform, a target sample calling unit, includes:
the instruction reading subunit is used for reading the notification instruction based on the intelligent sample library, acquiring a target sample according to a reading result, and simultaneously carrying out format conversion on the target sample according to a preset template to generate a sample label of the target sample and a sample expression of the target sample;
the sample determining subunit is used for matching an intelligent block for storing the target sample in the intelligent sample library based on the sample label of the target sample, and determining the target sample in the intelligent block based on the sample expression;
the instruction reading subunit is further used for reading the notification instruction and determining the calling sequence of the target sample;
and the sample calling sub-unit is used for sequencing the target samples based on the calling sequence, adding the sequencing sequence number and orderly calling the target samples based on the sequencing sequence number.
Preferably, a multi-device task scheduling central control management platform, a scheduling module, includes:
the robot matching unit is used for reading sample information of the target sample, determining the sample type of the target sample, and simultaneously matching a plurality of candidate intelligent robots capable of carrying the target sample in the robot information management library based on the sample type of the target sample;
the robot state determining unit is used for sending a state reading instruction to the plurality of candidate intelligent robots based on the central control system, reading state feedback information of the plurality of candidate intelligent robots based on the central control system, and dividing the plurality of candidate intelligent robots into idle candidate intelligent robots and busy candidate robots based on the state feedback information;
a fetch instruction generation unit configured to:
reading a target carrying capacity for carrying the target sample, determining the rated carrying capacity of the intelligent robot, and simultaneously obtaining a target ratio between the target carrying capacity and the rated carrying capacity;
determining a first target number for calling the candidate intelligent robots according to the target ratio;
when the target ratio is smaller than 1, a candidate intelligent robot is called;
otherwise, calling a rounding function to calculate based on the target ratio, and determining the first target number of the candidate intelligent robots according to the calculation result;
randomly selecting target candidate intelligent robots from the idle candidate intelligent robots based on the first target number of the candidate intelligent robots, and determining the intelligent numbers of the target candidate intelligent robots;
generating a calling instruction based on the intelligent numbers of the target candidate intelligent robots;
and the calling control unit is used for calling the first target candidate intelligent robot based on the calling instruction.
Preferably, a multi-device task scheduling central control management platform, a call instruction generating unit, includes:
an alarm subunit configured to:
acquiring the total number of the candidate intelligent robots, comparing the total number of the candidate intelligent robots with the first target number, and judging whether alarm operation is needed according to a comparison result;
when the total number of the candidate intelligent robots is equal to or greater than the first target number, judging that alarm operation is not needed;
otherwise, judging that alarm operation is needed, and generating an alarm signal based on the alarm operation;
a state determination subunit configured to:
after receiving the alarm signal, acquiring a target difference value between the first target number and the total number of candidate intelligent robots, and determining a second target number of the candidate intelligent robots based on the target difference value;
and acquiring the residual working time of the busy candidate robot, selecting a second target candidate intelligent robot with the minimum residual working time from the busy candidate robots, and calling the intelligent robot when the second target candidate intelligent robot finishes working.
Preferably, a multi-device task scheduling central control management platform, a scheduling module, includes:
an optimal path determination unit configured to:
respectively acquiring first position information of a thawing frame, second position information of an intelligent robot and third position information of an intelligent biological sample library;
the method comprises the steps of calling a target map of a laboratory, and marking first position information, second position information and third position information in the target map;
acquiring an optimal path of the intelligent robot in a target map based on the labeling result, and acquiring the path trend of the optimal path and the position of a path inflection point of the optimal path;
a conveyance control unit configured to:
generating a conveying control instruction based on the route trend of the optimal route and the route inflection point position of the optimal route;
and controlling the intelligent robot to carry the target sample to the thawing frame based on the carrying control instruction.
Preferably, a multi-device task scheduling central control management platform, a scheduling module, includes:
the sample state confirming unit is used for reading the target sample, determining the sample state of the target sample and determining the thawing time for thawing the target sample according to the sample state of the target sample;
the timing unit is used for timing the thawing of the target sample in the thawing frame based on the thawing time length for thawing the target sample, triggering the carrying instruction when the timing time length reaches the thawing time length, transmitting the carrying instruction to the intelligent robot based on the central control system, and controlling the intelligent robot to carry the target sample to the experimental equipment.
Preferably, a multi-device task scheduling central control management platform further includes:
the log recording unit is used for reading the scheduling execution data after the target order is completed, determining execution steps corresponding to the scheduling execution data, determining execution key data corresponding to each execution step, and constructing corresponding execution nodes according to the execution key data corresponding to each execution step, wherein the execution steps are in one-to-one correspondence with the execution nodes;
the association relation determining unit is used for acquiring the execution sequence of the execution steps and determining the association relation among the execution nodes based on the execution sequence;
the scheduling policy determining unit is used for determining the scheduling policy of the target order based on the association relation between the execution nodes and the execution nodes, acquiring the order type and the order characteristic of the target order, generating an order identifier based on the order type and the order characteristic of the target order, and storing the scheduling policy of the target order based on the order identifier;
and the scheduling policy invoking unit is used for invoking the scheduling policy based on the order label when the order to be scheduled similar to the target order exists, and taking the scheduling policy as a scheduling guide when the order to be scheduled is scheduled.
Compared with the prior art, the invention has the beneficial effects that:
1. receiving the target order through the upstream system, so that the target order is read and analyzed in the central control system, the target sample is accurately locked in the intelligent biological sample library, the target sample is conveyed to the thawing rack through the intelligent transferring robot, then the thawing rack is conveyed to experimental equipment for experiments, and the target sample is returned to the library after the experiments are finished, the equipment processing tasks are reasonably scheduled, the accumulation of detection tasks can be effectively reduced, the use efficiency of the equipment is improved, and the cost is reduced; the LIMS central control management platform is connected with the upstream ordering system, the intelligent biological sample library, the intelligent robot and the inspection equipment, so that manual intervention is greatly reduced, and the intelligent production is realized in a laboratory.
2. The candidate intelligent robots are determined, so that the efficiency of calling the intelligent robots is improved, the number of the candidate intelligent robots is determined by determining the target carrying capacity and the rated carrying capacity, the robots are effectively scheduled, and the scheduling efficiency and the intelligence of laboratory work are improved.
3. By reading the scheduling execution data, the determination of the execution key data of the corresponding execution step of the scheduling execution data is effectively realized, the execution node is effectively constructed, the storage of the execution key data is realized, and by generating the scheduling policy, the scheduling policy is beneficial to being fetched when the order to be scheduled consistent with the execution order is encountered again, the scheduling policy can be effectively used as scheduling guidance of the order to be scheduled in the execution scheduling process, and further used as scheduling reference of the order to be scheduled, so that the intelligence of laboratory scheduling is improved, and the production efficiency of a laboratory is guaranteed.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of a multi-device task scheduling central control management platform in an embodiment of the invention;
FIG. 2 is a block diagram of a scheduling module in a multi-device task scheduling central control management platform according to an embodiment of the present invention;
fig. 3 is a block diagram of a transmission module in a multi-device task scheduling central control management platform according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1:
the embodiment provides a multi-device task scheduling central control management platform, as shown in fig. 1, including:
the transmission module is used for receiving the target order from the upstream system and transmitting the target order to the central control system;
the sample determining module is used for initiating a notification instruction to the intelligent biological sample library according to the target order based on the central control system, and selecting a target sample from the intelligent biological sample library based on the notification instruction;
the scheduling module is used for scheduling the intelligent robot, carrying the target sample to the thawing rack based on the intelligent robot, and controlling the intelligent robot to carry the target sample to the experimental equipment based on the central control system after thawing the target sample, wherein the experimental equipment comprises a plurality of pieces of equipment, and data among the plurality of pieces of equipment are automatically transferred and executed when the target sample is subjected to experiments, so that the transfer of the target sample among the plurality of pieces of experimental equipment is completed;
meanwhile, after the experiment is completed, the robot is controlled to restore the target sample based on the central control system, and the experimental result is returned to the central control system.
In this embodiment, the target order may be an order such as a requirement for performing an experiment on the specimen, and may be a requirement including a biological specimen and performing an experiment on the biological specimen.
In this embodiment, the central control system may be a LIMS central control for controlling the tasks of picking up biological samples, robot scheduling, and experimental data analysis.
In this embodiment, the target specimen may be an experimental biological specimen determined based on the requirements of the target order.
In this embodiment, the intelligent biological sample library may be preset, contain a plurality of biological samples, and have a function of selecting biological samples.
In the embodiment, the upstream system orders to the LIMS center control, the LIMS center control informs the intelligent biological sample library of picking, the intelligent robot carries samples to the thawing frame, the LIMS center control calls the intelligent robot to carry samples to experimental equipment after timing thawing, meanwhile, equipment starting experimental parameters are placed in a designated folder, and after the equipment finishes an experiment, the LIMS center control analyzes a result file, and a task is issued or the intelligent robot is called to restore the library. And after the experiment is completed, the result is returned to the ordering system.
In this embodiment, the system further includes:
1. receiving an order of an upstream system, checking related data, and supporting ordering according to the planned time
2. Docking intelligent biological sample library supporting warehouse-in, warehouse-out and warehouse-back operations
3. The intelligent robot can be scheduled between devices, and the task number of the robot can be controlled
4. Control of experimental equipment to initiate experiments, failed retries
5. The device performs abnormality to notify the user in a short message or mail manner.
The beneficial effects of the technical scheme are as follows: receiving the target order through the upstream system, so that the target order is read and analyzed in the central control system, the target sample is accurately locked in the intelligent biological sample library, the target sample is conveyed to the thawing rack through the intelligent transferring robot, then the thawing rack is conveyed to experimental equipment for experiments, and the target sample is returned to the library after the experiments are finished, the equipment processing tasks are reasonably scheduled, the accumulation of detection tasks can be effectively reduced, the use efficiency of the equipment is improved, and the cost is reduced; the LIMS central control management platform is connected with the upstream ordering system, the intelligent biological sample library, the intelligent robot and the inspection equipment, so that manual intervention is greatly reduced, and the intelligent production is realized in a laboratory.
Example 2:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, as shown in fig. 2, the scheduling module further includes:
the parameter recording unit is used for automatically recording experimental parameters based on experimental equipment and placing the experimental parameters into a target folder when the intelligent robot carries the target sample to the experimental equipment;
and the analysis unit is used for analyzing the target folder based on the central control system to generate an experimental result when the experimental equipment completes the experiment on the target sample, and returning the experimental result to the upstream system.
In this embodiment, the target folder may be used to record experimental parameters corresponding to the current target order.
The beneficial effects of the technical scheme are as follows: the method effectively realizes the recording and analysis of experimental parameters, and improves the intelligence and effectiveness of experiments on target samples.
Example 3:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, as shown in fig. 3, a transmission module includes:
the order generation unit is used for reading the client requirements and generating a target order according to the client requirements;
an order receiving unit for receiving a target order based on an upstream system;
and the order transmission unit is used for transmitting the target order to the central control system based on the upstream system after the target order is received.
In this embodiment, the target order is generated based on customer needs by grasping key information of the customer needs to generate the target order.
The beneficial effects of the technical scheme are as follows: the accurate acquisition and efficient transmission of the target order are effectively realized, so that the intelligent production of a laboratory is improved.
Example 4:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, and a sample determining module includes:
the order reading unit is used for reading the target order based on the central control system and determining sample keywords and sample calling logic keywords in the target order;
the instruction generation unit is used for generating a first instruction element based on the sample keyword, generating a second instruction element based on the logic keyword, acquiring the association relation between the sample keyword and the sample calling logic keyword, and fusing the first instruction element and the second instruction element based on the association relation to generate a notification instruction;
the instruction initiating unit is used for initiating a notification instruction to the intelligent biological sample library;
a target sample calling unit, configured to:
determining a target sample and a retrieval sequence of the target sample according to the notification instruction based on the intelligent sample library;
and orderly calling the target samples in the intelligent sample library based on the calling sequence of the target samples.
In this embodiment, the first instruction element is determined based on a sample key, and may be used to control the retrieved target sample.
In this embodiment, the second instruction element is determined based on the sample retrieval logic key (i.e., the sequence, and/or order, etc. of retrieving samples), and may be used to control the order of retrieving target samples.
In this embodiment, the association relationship may be a relationship between a sample keyword and a sample retrieval logic keyword, for example, the sample keyword is: A. b, calling the logic keywords as follows: and firstly, A and then B, wherein the association relation is that A is called first and B is called second.
The beneficial effects of the technical scheme are as follows: the target samples can be effectively determined by determining the first instruction element, and the calling sequence among the target samples can be determined by determining the second instruction element, so that the obtained notification instruction is more accurate based on the first instruction element and the second instruction element, and the intelligence and the effectiveness of calling the target samples are effectively improved.
Example 5:
on the basis of embodiment 4, this embodiment provides a multi-device task scheduling central control management platform, and a target sample calling unit, including:
the instruction reading subunit is used for reading the notification instruction based on the intelligent sample library, acquiring a target sample according to a reading result, and simultaneously carrying out format conversion on the target sample according to a preset template to generate a sample label of the target sample and a sample expression of the target sample;
the sample determining subunit is used for matching an intelligent block for storing the target sample in the intelligent sample library based on the sample label of the target sample, and determining the target sample in the intelligent block based on the sample expression;
the instruction reading subunit is further used for reading the notification instruction and determining the calling sequence of the target sample;
and the sample calling sub-unit is used for sequencing the target samples based on the calling sequence, adding the sequencing sequence number and orderly calling the target samples based on the sequencing sequence number.
In this embodiment, the preset template may be set in advance, so as to implement format conversion of the target sample, and the purpose of format conversion of the target sample is to effectively identify and locate in the intelligent sample library, so as to ensure accurate identification of the intelligent sample library.
In this embodiment, the sample tag may be a tag for distinguishing the type of the target sample, and by determining the sample tag, the intelligent block storing the target sample can be effectively locked in the intelligent sample library, so that the target sample is determined in the intelligent block according to the sample expression.
The beneficial effects of the technical scheme are as follows: based on the reading of the notification instruction and the format conversion of the target sample, the locking and the calling of the target sample in the intelligent sample library are effectively realized, the calling sequence of the intelligent sample is determined, and the intelligence of calling the intelligent sample is improved.
Example 6:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, a scheduling module, including:
the robot matching unit is used for reading sample information of the target sample, determining the sample type of the target sample, and simultaneously matching a plurality of candidate intelligent robots capable of carrying the target sample in the robot information management library based on the sample type of the target sample;
the robot state determining unit is used for sending a state reading instruction to the plurality of candidate intelligent robots based on the central control system, reading state feedback information of the plurality of candidate intelligent robots based on the central control system, and dividing the plurality of candidate intelligent robots into idle candidate intelligent robots and busy candidate robots based on the state feedback information;
a fetch instruction generation unit configured to:
reading a target carrying capacity for carrying the target sample, determining the rated carrying capacity of the intelligent robot, and simultaneously obtaining a target ratio between the target carrying capacity and the rated carrying capacity;
determining a first target number for calling the candidate intelligent robots according to the target ratio;
when the target ratio is smaller than 1, a candidate intelligent robot is called;
otherwise, calling a rounding function to calculate based on the target ratio, and determining the first target number of the candidate intelligent robots according to the calculation result;
randomly selecting target candidate intelligent robots from the idle candidate intelligent robots based on the first target number of the candidate intelligent robots, and determining the intelligent numbers of the target candidate intelligent robots;
generating a calling instruction based on the intelligent numbers of the target candidate intelligent robots;
and the calling control unit is used for calling the first target candidate intelligent robot based on the calling instruction.
In this embodiment, since sample types of biological samples are different, robots for carrying biological samples are also different, and by determining sample types of target samples, screening of intelligent robot types is achieved.
In this embodiment, the state invoking instruction may be used to obtain current working states of the plurality of candidate intelligent robots, where the state feedback information is the current working states of the plurality of candidate intelligent robots, and the working states include: an idle state and a busy state.
In this embodiment, the rated movement may be the maximum movement that the intelligent robot can handle.
The beneficial effects of the technical scheme are as follows: the candidate intelligent robots are determined, so that the efficiency of calling the intelligent robots is improved, the number of the candidate intelligent robots is determined by determining the target carrying capacity and the rated carrying capacity, the robots are effectively scheduled, and the scheduling efficiency and the intelligence of laboratory work are improved.
Example 7:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, and a call instruction generating unit, including:
an alarm subunit configured to:
acquiring the total number of the candidate intelligent robots, comparing the total number of the candidate intelligent robots with the first target number, and judging whether alarm operation is needed according to a comparison result;
when the total number of the candidate intelligent robots is equal to or greater than the first target number, judging that alarm operation is not needed;
otherwise, judging that alarm operation is needed, and generating an alarm signal based on the alarm operation;
a state determination subunit configured to:
after receiving the alarm signal, acquiring a target difference value between the first target number and the total number of candidate intelligent robots, and determining a second target number of the candidate intelligent robots based on the target difference value;
and acquiring the residual working time of the busy candidate robot, selecting a second target candidate intelligent robot with the minimum residual working time from the busy candidate robots, and calling the intelligent robot when the second target candidate intelligent robot finishes working.
In this embodiment, the alarm operation may be one or more of sound, vibration, and light.
In this embodiment, the alarm signal may be a signal transmitted based on an alarm operation, so that the second target candidate intelligent robot can be grasped in time.
The beneficial effects of the technical scheme are as follows: when the number of the first targets corresponding to the candidate intelligent robots is smaller than the total number of the candidate intelligent robots, the second target candidate intelligent robots are selected from the busy candidate robots, and when the second target candidate intelligent robots finish working, the intelligent robots are called, the scheme effectively overcomes the defect that when the intelligent robots are insufficient, the busy candidate robots with the least residual working time are selected, and when the busy candidate robots finish working, the intelligent robots are called, so that the rationality and the uniformity of intelligent robot dispatching are effectively realized, and the efficiency and the order of robot dispatching are guaranteed.
Example 8:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, a scheduling module, including:
an optimal path determination unit configured to:
respectively acquiring first position information of a thawing frame, second position information of an intelligent robot and third position information of an intelligent biological sample library;
the method comprises the steps of calling a target map of a laboratory, and marking first position information, second position information and third position information in the target map;
acquiring an optimal path of the intelligent robot in a target map based on the labeling result, and acquiring the path trend of the optimal path and the position of a path inflection point of the optimal path;
a conveyance control unit configured to:
generating a conveying control instruction based on the route trend of the optimal route and the route inflection point position of the optimal route;
and controlling the intelligent robot to carry the target sample to the thawing frame based on the carrying control instruction.
In this embodiment, the target map may be a roadmap of a laboratory.
In this embodiment, the optimal route may be a route based on which the intelligent robot reaches the third position from the second position and the intelligent robot reaches the first position from the third position in the target map, the route having the shortest route time, the shortest route distance, and the minimum route inflection point.
The beneficial effects of the technical scheme are as follows: the optimal path can ensure that the intelligent robot is unobstructed in the carrying process, so that intelligent carrying of the target sample to the thawing frame by the robot based on carrying control instructions is accurately realized, and the intelligent and accuracy of laboratory dispatching are improved.
Example 9:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, a scheduling module, including:
the sample state confirming unit is used for reading the target sample, determining the sample state of the target sample and determining the thawing time for thawing the target sample according to the sample state of the target sample;
the timing unit is used for timing the thawing of the target sample in the thawing frame based on the thawing time length for thawing the target sample, triggering the carrying instruction when the timing time length reaches the thawing time length, transmitting the carrying instruction to the intelligent robot based on the central control system, and controlling the intelligent robot to carry the target sample to the experimental equipment.
The beneficial effects of the technical scheme are as follows: the target sample is thawed in the thawing frame for timing, and when the timing time length reaches the thawing time length, the intelligent robot is controlled to carry the target sample to experimental equipment based on the carrying instruction, so that the detection task accumulation is reduced, the equipment use efficiency is improved, and the cost is reduced.
Example 10:
on the basis of embodiment 1, this embodiment provides a multi-device task scheduling central control management platform, further including:
the log recording unit is used for reading the scheduling execution data after the target order is completed, determining execution steps corresponding to the scheduling execution data, determining execution key data corresponding to each execution step, and constructing corresponding execution nodes according to the execution key data corresponding to each execution step, wherein the execution steps are in one-to-one correspondence with the execution nodes;
the association relation determining unit is used for acquiring the execution sequence of the execution steps and determining the association relation among the execution nodes based on the execution sequence;
the scheduling policy determining unit is used for determining the scheduling policy of the target order based on the association relation between the execution nodes and the execution nodes, acquiring the order type and the order characteristic of the target order, generating an order identifier based on the order type and the order characteristic of the target order, and storing the scheduling policy of the target order based on the order identifier;
and the scheduling policy invoking unit is used for invoking the scheduling policy based on the order label when the order to be scheduled similar to the target order exists, and taking the scheduling policy as a scheduling guide when the order to be scheduled is scheduled.
In this embodiment, the key data may be data related to execution scheduling in the scheduled execution data, and the execution nodes may be used to store the execution key data, where each execution step has the execution key data, and the execution nodes are in one-to-one correspondence with the execution steps.
In this embodiment, the order identifier may be used as a distinction for the target order, so that the target order may be effectively identified.
The beneficial effects of the technical scheme are as follows: by reading the scheduling execution data, the determination of the execution key data of the corresponding execution step of the scheduling execution data is effectively realized, the execution node is effectively constructed, the storage of the execution key data is realized, and by generating the scheduling policy, the scheduling policy is beneficial to being fetched when the order to be scheduled consistent with the execution order is encountered again, the scheduling policy can be effectively used as scheduling guidance of the order to be scheduled in the execution scheduling process, and further used as scheduling reference of the order to be scheduled, so that the intelligence of laboratory scheduling is improved, and the production efficiency of a laboratory is guaranteed.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A multi-device task scheduling central control management platform, comprising:
the transmission module is used for receiving the target order from the upstream system and transmitting the target order to the central control system;
the sample determining module is used for initiating a notification instruction to the intelligent biological sample library according to the target order based on the central control system, and selecting a target sample from the intelligent biological sample library based on the notification instruction;
the scheduling module is used for scheduling the intelligent robot, carrying the target sample to the thawing rack based on the intelligent robot, and controlling the intelligent robot to carry the target sample to the experimental equipment based on the central control system after thawing the target sample, wherein the experimental equipment comprises a plurality of pieces of equipment, and data among the plurality of pieces of equipment are automatically transferred and executed when the target sample is subjected to experiments, so that the transfer of the target sample among the plurality of pieces of experimental equipment is completed;
meanwhile, after the experiment is completed, the robot is controlled to restore the target sample based on the central control system, and the experimental result is returned to the central control system.
2. The multi-device task scheduling central control management platform according to claim 1, wherein the scheduling module further comprises:
the parameter recording unit is used for automatically recording experimental parameters based on experimental equipment and placing the experimental parameters into a target folder when the intelligent robot carries the target sample to the experimental equipment;
and the analysis unit is used for analyzing the target folder based on the central control system to generate an experimental result when the experimental equipment completes the experiment on the target sample, and returning the experimental result to the upstream system.
3. The multi-device task scheduling central control management platform according to claim 1, wherein the transmission module comprises:
the order generation unit is used for reading the client requirements and generating a target order according to the client requirements;
an order receiving unit for receiving a target order based on an upstream system;
and the order transmission unit is used for transmitting the target order to the central control system based on the upstream system after the target order is received.
4. The multi-device task scheduling central management platform according to claim 1, wherein the sample determination module comprises:
the order reading unit is used for reading the target order based on the central control system and determining sample keywords and sample calling logic keywords in the target order;
the instruction generation unit is used for generating a first instruction element based on the sample keyword, generating a second instruction element based on the logic keyword, acquiring the association relation between the sample keyword and the sample calling logic keyword, and fusing the first instruction element and the second instruction element based on the association relation to generate a notification instruction;
the instruction initiating unit is used for initiating a notification instruction to the intelligent biological sample library;
a target sample calling unit, configured to:
determining a target sample and a retrieval sequence of the target sample according to the notification instruction based on the intelligent sample library;
and orderly calling the target samples in the intelligent sample library based on the calling sequence of the target samples.
5. The multi-device task scheduling central control management platform according to claim 4, wherein the target sample retrieval unit comprises:
the instruction reading subunit is used for reading the notification instruction based on the intelligent sample library, acquiring a target sample according to a reading result, and simultaneously carrying out format conversion on the target sample according to a preset template to generate a sample label of the target sample and a sample expression of the target sample;
the sample determining subunit is used for matching an intelligent block for storing the target sample in the intelligent sample library based on the sample label of the target sample, and determining the target sample in the intelligent block based on the sample expression;
the instruction reading subunit is further used for reading the notification instruction and determining the calling sequence of the target sample;
and the sample calling sub-unit is used for sequencing the target samples based on the calling sequence, adding the sequencing sequence number and orderly calling the target samples based on the sequencing sequence number.
6. The multi-device task scheduling central control management platform according to claim 1, wherein the scheduling module comprises:
the robot matching unit is used for reading sample information of the target sample, determining the sample type of the target sample, and simultaneously matching a plurality of candidate intelligent robots capable of carrying the target sample in the robot information management library based on the sample type of the target sample;
the robot state determining unit is used for sending a state reading instruction to the plurality of candidate intelligent robots based on the central control system, reading state feedback information of the plurality of candidate intelligent robots based on the central control system, and dividing the plurality of candidate intelligent robots into idle candidate intelligent robots and busy candidate robots based on the state feedback information;
a fetch instruction generation unit configured to:
reading a target carrying capacity for carrying the target sample, determining the rated carrying capacity of the intelligent robot, and simultaneously obtaining a target ratio between the target carrying capacity and the rated carrying capacity;
determining a first target number for calling the candidate intelligent robots according to the target ratio;
when the target ratio is smaller than 1, a candidate intelligent robot is called;
otherwise, calling a rounding function to calculate based on the target ratio, and determining the first target number of the candidate intelligent robots according to the calculation result;
randomly selecting target candidate intelligent robots from the idle candidate intelligent robots based on the first target number of the candidate intelligent robots, and determining the intelligent numbers of the target candidate intelligent robots;
generating a calling instruction based on the intelligent numbers of the target candidate intelligent robots;
and the calling control unit is used for calling the first target candidate intelligent robot based on the calling instruction.
7. The multi-device task scheduling central control management platform according to claim 1, wherein the call instruction generating unit comprises:
an alarm subunit configured to:
acquiring the total number of the candidate intelligent robots, comparing the total number of the candidate intelligent robots with the first target number, and judging whether alarm operation is needed according to a comparison result;
when the total number of the candidate intelligent robots is equal to or greater than the first target number, judging that alarm operation is not needed;
otherwise, judging that alarm operation is needed, and generating an alarm signal based on the alarm operation;
a state determination subunit configured to:
after receiving the alarm signal, acquiring a target difference value between the first target number and the total number of candidate intelligent robots, and determining a second target number of the candidate intelligent robots based on the target difference value;
and acquiring the residual working time of the busy candidate robot, selecting a second target candidate intelligent robot with the minimum residual working time from the busy candidate robots, and calling the intelligent robot when the second target candidate intelligent robot finishes working.
8. The multi-device task scheduling central control management platform according to claim 1, wherein the scheduling module comprises:
an optimal path determination unit configured to:
respectively acquiring first position information of a thawing frame, second position information of an intelligent robot and third position information of an intelligent biological sample library;
the method comprises the steps of calling a target map of a laboratory, and marking first position information, second position information and third position information in the target map;
acquiring an optimal path of the intelligent robot in a target map based on the labeling result, and acquiring the path trend of the optimal path and the position of a path inflection point of the optimal path;
a conveyance control unit configured to:
generating a conveying control instruction based on the route trend of the optimal route and the route inflection point position of the optimal route;
and controlling the intelligent robot to carry the target sample to the thawing frame based on the carrying control instruction.
9. The multi-device task scheduling central control management platform according to claim 1, wherein the scheduling module comprises:
the sample state confirming unit is used for reading the target sample, determining the sample state of the target sample and determining the thawing time for thawing the target sample according to the sample state of the target sample;
the timing unit is used for timing the thawing of the target sample in the thawing frame based on the thawing time length for thawing the target sample, triggering the carrying instruction when the timing time length reaches the thawing time length, transmitting the carrying instruction to the intelligent robot based on the central control system, and controlling the intelligent robot to carry the target sample to the experimental equipment.
10. The multi-device task scheduling central management platform of claim 1, further comprising:
the log recording unit is used for reading the scheduling execution data after the target order is completed, determining execution steps corresponding to the scheduling execution data, determining execution key data corresponding to each execution step, and constructing corresponding execution nodes according to the execution key data corresponding to each execution step, wherein the execution steps are in one-to-one correspondence with the execution nodes;
the association relation determining unit is used for acquiring the execution sequence of the execution steps and determining the association relation among the execution nodes based on the execution sequence;
the scheduling policy determining unit is used for determining the scheduling policy of the target order based on the association relation between the execution nodes and the execution nodes, acquiring the order type and the order characteristic of the target order, generating an order identifier based on the order type and the order characteristic of the target order, and storing the scheduling policy of the target order based on the order identifier;
and the scheduling policy invoking unit is used for invoking the scheduling policy based on the order label when the order to be scheduled similar to the target order exists, and taking the scheduling policy as a scheduling guide when the order to be scheduled is scheduled.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180180635A1 (en) * | 2016-12-22 | 2018-06-28 | Counsyl, Inc. | Automatic diagnostic laboratory and laboratory information management system for high throughput |
| CN108227578A (en) * | 2017-12-29 | 2018-06-29 | 上海移远通信技术股份有限公司 | Automated test control system and method |
| CN112863135A (en) * | 2020-12-30 | 2021-05-28 | 无锡市疾病预防控制中心 | Experimental process prompting and early warning system of experimental assistant robot |
| CN112951230A (en) * | 2021-02-08 | 2021-06-11 | 谈斯聪 | Remote and autonomous experimental robot device, management system and method |
| CN113777336A (en) * | 2021-09-08 | 2021-12-10 | 广州赛特智能科技有限公司 | Automatic detection system and method for biological specimen |
| CN115248329A (en) * | 2021-04-28 | 2022-10-28 | 南京智欧智能技术研究院有限公司 | Automatic sterile laboratory and experimental method |
| CN115847394A (en) * | 2022-10-21 | 2023-03-28 | 圣名科技(广州)有限责任公司 | Method and device for controlling mechanical arm to grab object, electronic equipment and storage medium |
| CN116160452A (en) * | 2023-03-23 | 2023-05-26 | 研华科技(中国)有限公司 | Intelligent factory robot control method |
| CN116307546A (en) * | 2023-02-20 | 2023-06-23 | 塔米智能科技（北京）有限公司 | Task intelligent decision system based on robot community |
-
2023
- 2023-08-04 CN CN202310980604.6A patent/CN116859788A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180180635A1 (en) * | 2016-12-22 | 2018-06-28 | Counsyl, Inc. | Automatic diagnostic laboratory and laboratory information management system for high throughput |
| CN108227578A (en) * | 2017-12-29 | 2018-06-29 | 上海移远通信技术股份有限公司 | Automated test control system and method |
| CN112863135A (en) * | 2020-12-30 | 2021-05-28 | 无锡市疾病预防控制中心 | Experimental process prompting and early warning system of experimental assistant robot |
| CN112951230A (en) * | 2021-02-08 | 2021-06-11 | 谈斯聪 | Remote and autonomous experimental robot device, management system and method |
| CN115248329A (en) * | 2021-04-28 | 2022-10-28 | 南京智欧智能技术研究院有限公司 | Automatic sterile laboratory and experimental method |
| CN113777336A (en) * | 2021-09-08 | 2021-12-10 | 广州赛特智能科技有限公司 | Automatic detection system and method for biological specimen |
| CN115847394A (en) * | 2022-10-21 | 2023-03-28 | 圣名科技(广州)有限责任公司 | Method and device for controlling mechanical arm to grab object, electronic equipment and storage medium |
| CN116307546A (en) * | 2023-02-20 | 2023-06-23 | 塔米智能科技（北京）有限公司 | Task intelligent decision system based on robot community |
| CN116160452A (en) * | 2023-03-23 | 2023-05-26 | 研华科技(中国)有限公司 | Intelligent factory robot control method |
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