CN114758765A

CN114758765A - Medical logistics robot intelligent scheduling method based on multi-dimensional state

Info

Publication number: CN114758765A
Application number: CN202210328270.XA
Authority: CN
Inventors: 王西恩; 马永礼; 张晓宇
Original assignee: Chengdu Ruihua Kangyuan Technology Co ltd
Current assignee: Chengdu Ruihua Kangyuan Technology Co ltd
Priority date: 2022-03-30
Filing date: 2022-03-30
Publication date: 2022-07-15

Abstract

The invention relates to the field of robot scheduling, and particularly discloses a medical logistics robot intelligent scheduling method based on a multidimensional state, which defines all states and time of a robot, changes event setting by a multidimensional robot condition, formulates the robot according to the relation between circulation among robot states and events according to hospital environment requirements, and simultaneously distributes the robot to each robot to execute according to formulated orders.

Description

Medical logistics robot intelligent scheduling method based on multi-dimensional state

Technical Field

The invention relates to the field of robot scheduling, in particular to a medical logistics robot intelligent scheduling method based on a multi-dimensional state.

Background

The traditional robot scheduling system more realizes task allocation, path planning, automatic charging and the like of a plurality of robots of the same type in the same scene.

The hospital environment has a plurality of requirements, and different types of robots are involved to realize different service scenes. The disinfection robot disinfects to subregion, and the robot of checking is checked storehouse goods and materials, and clean goods and materials delivery robot realizes that goods and materials from the storehouse to the transport task of operating room, and the robot of patrolling and delivering realizes that the tour moves in order to satisfy the interim goods and materials demand of operating room in the operating room region, and filth robot realizes transporting recovery room or disinfection room to the apparatus, filth etc. after the operation.

Disclosure of Invention

Aiming at the defects in the prior art, the invention provides an intelligent scheduling method of a medical logistics robot based on a multi-dimensional state.

In order to achieve the purpose of the invention, the invention adopts the technical scheme that:

a medical logistics robot intelligent scheduling method based on a multi-dimensional state comprises the following steps:

s1, defining all states and events of the robot, and setting the relationship between the circulation among the states of the robot and the events;

s2, making different orders according to different medical logistics requirements, and caching the orders to an order queue;

s3, sequentially distributing the orders in the order queue to different robots to be executed according to different states of the robots;

And S4, returning the robot to the rest station through automatic navigation after the task is executed.

Further, the event in S1 is set by a multidimensional robot condition change, including a change in the robot position, a change in the health condition of the robot, and an operation instruction of the business system.

Further, the relationship between the circulation and the event between the robot states in S1 is:

the first state is converted into a second state after passing through a first trigger event;

the second state flow is converted into a first event for processing, and is converted into a third state after passing through a second trigger event;

and repeating the steps, sequentially converting the first state into the nth state and executing the nth event processing.

Further, the specific manner of S2 is as follows:

s21, receiving service orders, including goods receiving and dispatching orders, checking orders, disinfecting orders, dirt recycling orders and dirt recycling and returning orders;

s22, performing order verification in a unified manner, and verifying whether the order format is legal or not and whether an order destination exists or not;

and S23, selecting different robots according to the service type, the electricity consumption and the distance condition according to the verified orders and distributing and executing the robots.

Further, the specific rule of S23 is:

specifying the robot type: executing a task according to whether the robot is designated by an order issued by the service; selecting the robot if the robot is specified in the order; if the robot is not specified, firstly specifying the type of the robot to be used according to the operation type of the robot and the order business type;

Specifying a robot: preferentially selecting an idle robot according to a scheduling principle, and detecting whether the position of the selected idle robot is legal, whether the idle robot is charging and whether the number of orders to be executed exceeds the maximum number;

calculating the starting position time consumption: calculating the time consumed from the current position to the destination; the time for opening and closing the automatic door and the time for passing the automatic door are added when the automatic door of the hospital is required to pass in the route; adding the time for waiting for the elevator, the time for getting in and out of the elevator and the running time of the elevator to the cross-floor requirement of taking the elevator in the route and accumulating;

selecting a shortest path: selecting a path which consumes the least time from the calculated consumed time of all the routes as a robot execution path;

if the order is successfully created, judging whether the order is to be executed in the state machine, if so, adding the order into an order queue, otherwise, immediately executing the order; if the robot is charging, the charging is cancelled first and then the order is executed.

Further, the order execution rule in S23 is:

in the task execution process, if the channel is a normal channel, the order is executed according to the order requirement;

and if a plurality of robots pass through the same area and the same aisle simultaneously in the same area, the robots can be automatically dispatched and avoided according to the task priority principle.

Further, the automatic scheduling avoidance limit conditions are as follows:

the channel is the same as the dead end, and the robot can only return along the original path after entering;

the passage is narrow, or sundries are often placed on one side of the passage, and the passage space can only pass through one robot at the same time.

Further, the automatic scheduling avoiding mode is as follows:

a plurality of robots run in the same direction and can enter a channel;

the robots running in opposite directions exist, the robots outside the channel need to avoid the robots in the single channel, and the robots run in after coming out of the single channel;

a stationary robot is arranged in the passage, or the destination of the robot outside the passage does not pass through the position of the stationary robot, and then the robot is allowed to enter; and if the user needs to pass through the position of the mobile phone, the mobile phone is avoided and enters after the mobile phone comes out.

Further, in S3, the specific manner of sequentially allocating the orders in the order queue to different robots for execution according to different states of the robots is as follows:

if the order which passes the verification does not specify the robot, executing the following steps to select the robot to be used;

s311, selecting all idle robots: appointing a robot in an idle state with a matched type according to the robot work type and the order service type;

S312, calculating the total time consumption from the current position of each selected idle robot to the destination: directly calculating the total consumed time of a starting point and a destination on the same floor; calculating the total time consumption of the time consumption required by controlling the elevator and taking the elevator and the time consumption of each floor during navigation when the floors are crossed;

s313, selecting the robot with the shortest time consumption from the robots with the calculated total time consumption as the robot for executing the task;

s314, creating an execution order and sending the execution order to a state machine for execution;

verifying that the robot performing the task has been specified in the passing order, performing the following steps to select the robot to be used:

s321, inquiring whether the robot has a task order being executed, and if not, adding a new order into an order queue;

s323, judging whether the robot executes a charging task: when the charging task is executed, charging is canceled first, and then other order tasks are executed;

s324, judging whether the order queue of the robot has a rejection order: if the rejected order exists, the new order is inserted into the back of the rejected order, and the new order is executed after the rejected order is executed.

The invention has the following beneficial effects:

the method makes unified rules for managing various tasks which are complex, crossed and relatively independent, so that all robots and tasks work orderly in the same environment.

Drawings

Fig. 1 is a flow diagram illustrating an intelligent scheduling method for a medical logistics robot based on a multidimensional state according to the invention.

FIG. 2 is a schematic diagram of an overall order flow according to an embodiment of the present invention.

FIG. 3 is a flow chart of an embodiment of the invention.

FIG. 4 is a schematic view of a process for recycling sewage according to an embodiment of the present invention.

FIG. 5 is a schematic view of a sterilization process according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.

A medical logistics robot intelligent scheduling method based on multi-dimensional state is disclosed, as shown in fig. 1, and comprises the following steps:

specifically, the life cycles of all robots are uniformly managed by a state machine; the state machine is mainly composed of two elements, namely an organic state (RobotState) and an event (RobotEvent), and switching between the states is driven by the event. Setting the relation between the flow between the states and the event in the state machine; start state (from) - > target state (to), trigger event (on) and event processing (execute).

Events (RobotEvent) are set by external conditions of multiple dimensions to change the robot position, the health status of the robot, operational commands of the business system (such as shipping, receiving, inventory, disinfection, unloading, charging, etc.).

Specifically, as shown in FIG. 2

The relationship between the circulation and the event among the states of the robot is as follows:

all business orders have unified entry as shown in fig. 2, which includes the following steps:

s21, the dispatching system receives orders of the service system, such as goods receiving and dispatching orders, checking orders, disinfection orders, dirt recovery return orders and the like.

S22, uniformly executing order verification, wherein the verification rule is as follows;

1. the order starting location cannot be empty and the starting location operation type cannot be empty.

2. The type of the start position operation cannot be out of the range of the operation allowed by the robot.

3. And verifying whether the order with the number exists in the order queue.

4. And verifying whether the node related to the current order exists in the dispatching system and whether the node type conforms to the operation type.

5. And if the robot is specified in the order, verifying whether the robot exists or not and starting the state or not.

And S23, selecting different robots according to the service type, the power consumption and the distance condition according to the verified orders and distributing and executing the robots.

In performing the allocation, the following rules are employed,

calculating the time consumption of the starting position: calculating the time consumption from the current position to the destination; the time for opening and closing the automatic door and the time for passing the automatic door are added when the automatic door of the hospital is required to pass in the route; adding the time for waiting for the elevator, the time for getting in and out of the elevator and the running time of the elevator to the cross-floor requirement of taking the elevator in the route and accumulating;

Selecting a shortest path: selecting a path with the least consumed time from the calculated consumed time of all the routes as a robot execution path;

if the order is successfully established, judging whether the order is to be executed in the state machine, if so, adding the order into an order queue, otherwise, immediately executing the order; if the robot is charging, the order is executed after the charging is cancelled.

S3, sequentially distributing the orders in the order queue to different robots to be executed according to different states of the robots, as shown in FIG. 3;

the state machine executes the orders in the order queue and each link in the middle of the orders in sequence until the task is completed, and the specific execution mode is as follows:

s31, when the robot is not specified in the verified order, the following steps are performed to select the robot to be used.

S311, selecting all idle robots: and according to the robot work type and the order business type, the robot in the idle state in the matching type is specified.

S312, calculating the total time consumption from the current position of each selected idle robot to the destination: directly calculating the total consumed time of a starting point and a destination on the same floor; the total time consumption is calculated by adding the time consumption required for controlling the elevator and taking the elevator to the time consumption required for navigation of each floor when the floor is crossed.

And S313, selecting the robot with the shortest time consumption from the robots with the calculated total time consumption as the robot for executing the task.

And S314, creating an execution order and sending the execution order to a state machine for execution.

And S32, verifying that the robot executing the task is specified in the passing order.

S321, inquiring whether the executing task order exists in the state machine.

And S322, adding the new order into the order queue.

S323, judging whether the robot executes a charging task: when the charging task is executed, charging is canceled first, and then other order tasks are executed.

S324, judging whether the order queue of the robot has a rejection order: if the rejected order exists, the new order is inserted behind the rejected order, and the new order is executed after the rejected order is executed.

In the task execution process, when a plurality of robots are in the same area and the same passageway, the robots can be automatically dispatched and avoided according to the task priority principle when passing through the passageway.

The robot arrives at the destination or waits for receiving goods, or starts disinfection, or starts inventory, or starts dirt recovery, etc., and performs the respective tasks, taking the dirt recovery and disinfection process as an example,

as shown in the flow chart of the sewage recovery treatment in figure 4,

1. The sewage robot receives the sewage order application.

2. And the sewage robot navigates to the station where the sewage material vehicle is located according to the scheduling.

3. And the dispatching center sends a material vehicle docking command after receiving the information that the sewage robot arrives at the station.

4. The dirt robot executes the accurate navigation method to drill to the bottom of the material vehicle and automatically lift the material vehicle.

5. And after receiving the message of successful material vehicle lifting, the dispatching center generates a navigation route and sends a navigation command to the robot to convey the dirt to the dirt recycling station.

6. After the sewage robot reaches the sewage recycling station, the sewage can be unloaded manually, and the next transportation task can be continued after the material vehicle is also automatically unloaded.

A schematic of the sterilization order flow process shown in figure 5.

1. After the disinfection robot is assigned to a disinfection task, the disinfection robot goes to the first disinfection station and starts disinfection after arrival.

2. And after the station finishes the disinfection task, automatically going to the next disinfection station, and continuing to disinfect until all stations are disinfected.

3. According to the state that the disinfectant returned by the sensor is insufficient, the disinfection robot can automatically go to a disinfectant supplementing site to supplement the disinfectant, and then continues to disinfect.

In the process of executing tasks, a hospital passageway is narrow, certain sickbeds are often placed in the passageway temporarily, only one robot can pass through the passageway at the same time, and dead figures exist in part of the passageways; when multiple robots send goods simultaneously, the dispatching and avoiding are needed. The principle of judging whether scheduling is needed is as follows:

a. The channel is the same as the dead end, and the robot can only return along the original path after entering;

b. the passage is narrow, or sundries are often placed on one side of the passage, and the passage space can only pass through one robot at the same time.

Under the condition of meeting the condition of scheduling avoidance,

1. multiple robots run in the same direction and can enter a single channel.

2. The robots running oppositely exist, the robots outside the single channel need to avoid the robots in the single channel, and the robots run in after coming out of the single channel.

3. A static robot (waiting for goods receiving and the like) is arranged in the single channel; allowing entry if the robot destination outside the corridor does not pass the stationary robot position; if the user needs to pass through the position of the mobile phone, the mobile phone is avoided and enters after the mobile phone is out.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto and changes may be made without departing from the scope of the invention in its aspects.

Claims

1. A medical logistics robot intelligent scheduling method based on a multi-dimensional state is characterized by comprising the following steps:

and S4, returning the robot navigation of which the task is finished to the rest station.

2. The method for intelligently scheduling the medical logistics robot based on the multi-dimensional state as claimed in claim 1, wherein the event in S1 is set by multi-dimensional robot condition change, and includes a change of a robot position, a change of a robot health condition and an operation instruction of a business system.

3. The medical logistics robot intelligent scheduling method based on multi-dimensional state as claimed in claim 1, wherein the relationship between circulation and events among robot states in S1 is:

4. The medical logistics robot intelligent scheduling method based on multi-dimensional state as claimed in claim 1, wherein the specific manner of S2 is as follows:

5. The medical logistics robot intelligent scheduling method based on multi-dimensional state as claimed in claim 4, wherein the specific rules of S23 are as follows:

Specifying the robot type: executing a task according to whether the robot is designated by the service issued order; selecting the robot if the robot is specified in the order; if the robot is not specified, firstly, the type of the robot to be used is specified according to the work type of the robot and the order business type;

specifying a robot: preferentially selecting an idle robot according to a scheduling principle, and detecting whether the position of the selected idle robot is legal, whether the idle robot is charging or not and whether the number of orders to be executed exceeds the maximum number or not;

calculating the starting position time consumption: calculating the time consumed from the current position to the destination; the route needs to pass through the hospital automatic door, and the total consumed time is the sum of the consumed time from the current position to the destination and the time for opening and closing the automatic door and the time for passing through the automatic door; the route needs to take an elevator to cross floors, and the total consumed time is the sum of the consumed time from the current position to the destination, the elevator waiting time, the elevator entering and exiting time and the elevator running time;

6. The medical logistics robot intelligent scheduling method based on multi-dimensional state as claimed in claim 1, wherein the rules for order execution in S23 are:

and if a plurality of robots are in the same area and the same aisle and pass through the same aisle, the robots are automatically dispatched and avoided according to a task priority principle.

7. The medical logistics robot intelligent scheduling method based on the multi-dimensional state as claimed in claim 6, wherein the limiting conditions for automatic scheduling avoidance are as follows:

the channel is a dead end, and the robot can only return in the original way after entering;

the passage is narrow, or a barrier is arranged on one side of the passage, or the passage space can only pass through one robot at the same time.

8. The medical logistics robot intelligent scheduling method based on the multi-dimensional state as claimed in claim 7, wherein the automatic scheduling avoidance mode is:

a plurality of robots run in the same direction and can enter a channel;

A stationary robot is arranged in the passage, or the destination of the robot outside the passage does not pass through the position of the stationary robot, and then the robot is allowed to enter; and if the robot needs to pass through the position of the immovable robot in the channel, the robot is avoided from entering the waiting channel after coming out.

9. The medical logistics robot intelligent scheduling method based on multi-dimensional state as claimed in claim 8, wherein the specific way in S3 of allocating orders in the order queue to different robots in sequence for execution according to different states of the robots is:

s324, judging whether the order form of the robot has a rejected order form: if the rejected order exists, the new order is inserted into the back of the rejected order, and the new order is executed after the rejected order is executed.