Robot quantity adjustment method, device, equipment and storage medium

Abstract

The present application discloses a method, device, equipment and storage medium for adjusting the number of robots, which belongs to the field of robots. The method comprises: first determining the first waiting time and the first attendance time of each robot in the target area within a first preset time, and then adjusting the number of robots in the target area according to the first waiting time and the first attendance time of the M robots. Wherein, M is a positive integer, the first waiting time is the total time that the corresponding robot waits to perform the delivery task within the first preset time, and the first attendance time is the total time that the corresponding robot performs the delivery task within the first preset time. In this way, the number of robots in the target area can be automatically and reasonably adjusted according to the first waiting time and the first attendance time of the M robots, so that the resource utilization rate of the robots and the efficiency of task completion in the target area can be better balanced.

Description

Technical Field

[0001] The present application relates to the field of robots, and in particular to a method, device, equipment and storage medium for adjusting the number of robots. Background Art

[0002] As the complexity of robotic tasks continues to increase, a single robot can no longer complete complex and tedious tasks on its own. Consequently, the collaborative work of multiple robots has become a growing trend in robotics development. For example, deploying a specific number of robots within a specific area to complete item delivery tasks fully utilizes robot resources and improves task completion efficiency within that area.

[0003] In the prior art, designers typically manually determine the number of robots needed to deliver items to a target area based on experience. For example, they determine the number of robots needed based on factors such as the target area's size and the number of delivery orders. Then, based on the set number of robots, multiple robots are deployed within the target area, allowing them to collaborate and perform the delivery task.

[0004] However, the number of robots set based on experience may be too many or too few, resulting in low robot resource utilization or low task completion efficiency within the target area. For example, if the number of robots is too large, some robots will be idle, resulting in wasted robot resources and low resource utilization. Alternatively, if the number of robots is too small, multiple robots may not complete tasks in a timely manner, resulting in low task completion efficiency within the target area. Summary of the Invention

[0005] This application provides a robot quantity adjustment method, apparatus, device, and storage medium that can automatically and reasonably adjust the number of robots in a target area based on the total waiting time for each robot to perform a delivery task within a preset time period and the total time it takes to perform a delivery task, thereby achieving a good balance between the resource utilization rate and task completion efficiency of the robots. The technical solution is as follows:

[0006] In a first aspect, a method for adjusting the number of robots is provided, the method comprising:

[0007] For M robots in a target area, determine a first waiting time and a first attendance time for each of the M robots within a first preset time period, where M is a positive integer, the first waiting time is the total time the corresponding robot waits to perform a delivery task within the first preset time period, and the first attendance time is the total time the corresponding robot performs a delivery task within the first preset time period;

[0008] The number of robots in the target area is adjusted according to the first waiting time and the first attendance time of the M robots.

[0009] As an example, adjusting the number of robots in the target area according to the first waiting time and the first attendance time of the M robots includes:

[0010] If the number of robots among the M robots whose first waiting time is greater than the first time threshold is less than or equal to the number threshold, triggering a first instruction, wherein the first instruction is used to instruct to increase the number of robots in the target area;

[0011] If the number of robots among the M robots whose first waiting time is greater than the first time threshold is greater than the number threshold, a second instruction is triggered according to the first attendance time of the M robots, and the second instruction is used to instruct to reduce the number of robots in the target area.

[0012] As an example, triggering the second instruction according to the first attendance duration of the M robots includes:

[0013] Determine a first number, where the first number is the number of robots among the M robots whose first attendance duration is greater than a second attendance threshold;

[0014] The second instruction is triggered according to the first number, and the second instruction is used to instruct to reduce the number of robots in the target area to the first number.

[0015] As an example, after triggering the first instruction, the method further includes:

[0016] If the number of robots in the target area increases from the M robots to N robots, determining a second waiting time within a second preset time for each of the N robots, where N is a positive integer and N is greater than M, and the second preset time is after the first preset time;

[0017] If the number of robots among the N robots whose second waiting time is longer than the first waiting time threshold is less than or equal to the number threshold, triggering the first instruction;

[0018] If the number of robots among the N robots whose second waiting time is greater than the first time threshold is greater than the number threshold, the second attendance time of each of the N robots within the second preset time is determined, and the second instruction is triggered according to the second attendance time of the N robots.

[0019] As an example, the method further includes:

[0020] For the target items to be delivered, determine the target delivery location, target pickup location, and target delivery warehouse quantity of the target items;

[0021] Determining a target robot for delivering the target item from the robots in the target area based on the target number of delivery bins, the working status of each robot in the target area, and the number of free bins, and determining a target bin for storing the target item from the free bins of the target robots, wherein each robot in the target area includes at least one bin for storing items;

[0022] Controlling the target robot to go to the target receiving location to search for the target item;

[0023] In a case where the target warehouse stores the target item, the target robot is controlled to move from the target receiving position to the target delivery position to deliver the target item.

[0024] As an example, the cargo bin state of each cargo bin in the at least one cargo bin includes an idle state, a locked state, and an occupied state, and the idle cargo bin is a cargo bin in the corresponding robot that is in the idle state;

[0025] After determining the target cargo bin for storing the target object from the free cargo bins of the target robot, the method further includes:

[0026] Switching the cargo hold state of the target cargo hold from the idle state to the locked state;

[0027] Before controlling the target robot to move from the target receiving location to the target delivery location to deliver the target item, the method further includes:

[0028] The warehouse state of the target warehouse is switched from the locked state to the occupied state.

[0029] As an example, the working state of each robot includes at least a waiting state, a searching state, and a delivery state, wherein the waiting state indicates that the corresponding robot is waiting to go to the receiving location to search for items to be delivered, the searching state indicates that the corresponding robot is going to the receiving location to search for items to be delivered or receiving items to be delivered at the receiving location, and the delivery state indicates that the corresponding robot is going from the receiving location to the receiving location to deliver items to be delivered or issuing items to be delivered at the receiving location;

[0030] The step of determining a target robot for delivering the target item from the robots in the target area according to the target number of delivery bins, the working status of each robot in the target area, and the number of free bins includes:

[0031] If there is at least one first robot in the target area that is in the search state and has a number of free cargo bins greater than or equal to the target delivery cargo bin number, determining the target robot from the at least one first robot;

[0032] If there is no at least one first robot in the target area that is in the searching state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses, then at least one second robot in the waiting state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses is determined from the robots in the target area, and the target robot is determined from the at least one second robot.

[0033] As an example, determining the target robot from the at least one second robot includes:

[0034] The second robot with the shortest target state duration among the at least one second robot is determined as the target robot, where the target state duration is the duration after the working state of the corresponding robot switches from the delivery state to the waiting state.

[0035] In a second aspect, a robot quantity adjustment device is provided, the device comprising:

[0036] a first determination module configured to determine, for M robots in a target area, a first waiting time and a first attendance time of each of the M robots within a first preset time period, where M is a positive integer, the first waiting time being the total time the corresponding robot waits to perform a delivery task within the first preset time period, and the first attendance time being the total time the corresponding robot performs a delivery task within the first preset time period;

[0037] An adjustment module is used to adjust the number of robots in the target area according to the first waiting time and the first attendance time of the M robots.

[0038] As an example, the adjustment module is further configured to trigger a first instruction to increase the number of robots in the target area if the number of robots among the M robots whose first waiting time is greater than the first time threshold is less than or equal to a number threshold;

[0039] If the number of robots among the M robots whose first waiting time is greater than the first time threshold is greater than the number threshold, a second instruction is triggered according to the first attendance time of the M robots, and the second instruction is used to instruct to reduce the number of robots in the target area.

[0040] As an example, the adjustment module is further configured to determine a first number, where the first number is the number of robots among the M robots whose first attendance duration is greater than a second attendance threshold;

[0041] The second instruction is triggered according to the first number, and the second instruction is used to instruct to reduce the number of robots in the target area to the first number.

[0042] As an example, the robot quantity adjustment device further includes a second determination module, a first trigger module and a second trigger module.

[0043] The second determining module is configured to determine a second waiting time within a second preset time period for each of the N robots if the number of robots in the target area increases from the M robots to N robots, where N is a positive integer and greater than M, and the second preset time period is later than the first preset time period;

[0044] The first triggering module is configured to trigger the first instruction if the number of robots among the N robots whose second waiting time is greater than the first waiting time threshold is less than or equal to the number threshold;

[0045] The second trigger module is used to determine the second attendance duration of each of the N robots within the second preset duration if the number of robots among the N robots whose second waiting duration is greater than the first duration threshold is greater than the number threshold, and trigger the second instruction according to the second attendance duration of the N robots.

[0046] As an example, the robot quantity adjustment device further includes a third determination module, a fourth determination module, a first control module, and a second control module:

[0047] The third determining module is used to determine the target delivery location, target receiving location and target delivery warehouse quantity of the target item to be delivered;

[0048] The fourth determination module is configured to determine a target robot for delivering the target item from the robots within the target area, and determine a target warehouse for storing the target item from the target robots' free warehouses, based on the target number of delivery warehouses, the operating status of each robot within the target area, and the number of free warehouses, wherein each robot within the target area includes at least one warehouse for storing items.

[0049] The first control module is used to control the target robot to go to the target receiving location to search for the target item;

[0050] The second control module is configured to control the target robot to move from the target receiving position to the target delivery position to deliver the target item when the target warehouse stores the target item.

[0051] As an example, the warehouse status of each warehouse in the at least one warehouse includes an idle state, a locked state, and an occupied state, and the idle warehouse is a warehouse in the corresponding robot that is in an idle state; the robot quantity adjustment device further includes a first switching module and a second switching module:

[0052] The first switching module is configured to switch the cargo hold state of the target cargo hold from the idle state to the locked state;

[0053] The second switching module is configured to switch the cargo hold state of the target cargo hold from the locked state to the occupied state.

[0054] As an example, the working state of each robot includes at least a waiting state, a searching state, and a delivery state. The waiting state indicates that the corresponding robot is waiting to go to the receiving location to search for items to be delivered. The searching state indicates that the corresponding robot is going to the receiving location to search for items to be delivered or receiving items to be delivered at the receiving location. The delivery state indicates that the corresponding robot is going from the receiving location to the receiving location to deliver items to be delivered or is distributing items to be delivered at the receiving location.

[0055] The fourth determining module is further configured to determine the target robot from among the robots in the target area if there is at least one first robot in the search state and the number of free cargo bins of which is greater than or equal to the target number of delivery cargo bins;

[0056] If there is no at least one first robot in the target area that is in the searching state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses, then at least one second robot in the waiting state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses is determined from the robots in the target area, and the target robot is determined from the at least one second robot.

[0057] As an example, the fourth determination module is also used to determine the second robot with the shortest target state duration among the at least one second robot as the target robot, and the target state duration is the duration after the working state of the corresponding robot switches from the delivery state to the waiting state.

[0058] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the above-mentioned robot quantity adjustment method when executed by the processor.

[0059] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned robot quantity adjustment method is implemented.

[0060] The beneficial effects of the technical solution provided by the embodiments of the present application are:

[0061] In an embodiment of the present application, the first waiting time and first attendance time of each of the M robots in a target area within a first preset time period can be first determined, and then the number of robots in the target area can be adjusted based on the first waiting time and first attendance time of the M robots. Where M is a positive integer, the first waiting time is the total time the corresponding robot waits to perform a delivery task within the first preset time period, and the first attendance time is the total time the corresponding robot performs a delivery task within the first preset time period. In this way, the number of robots in the target area can be automatically adjusted based on the total time each robot waits to perform a delivery task within the preset time period and the total time each robot performs a delivery task. Because the first waiting time and first attendance time can reflect the task completion efficiency and the resource utilization rate of the robots within the target area, the number of robots in the target area automatically adjusted based on the first waiting time and first attendance time of each robot is more reasonable, thereby achieving a good balance between the resource utilization rate of the robots and the task completion efficiency within the target area, and both are high. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0063] Figure 1 This is a flow chart of a method for adjusting the number of robots provided in an embodiment of the present application;

[0064] Figure 2 This is a flow chart of an item delivery method provided in an embodiment of the present application;

[0065] Figure 3 This is a schematic structural diagram of a robot quantity adjustment device provided in an embodiment of the present application;

[0066] Figure 4 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0067] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0068] It should be understood that the “multiple” mentioned in this application refers to two or more. In the description of this application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in order to facilitate the clear description of the technical solution of this application, words such as “first” and “second” are used to distinguish between identical or similar items with basically the same functions and effects. Those skilled in the art can understand that words such as “first” and “second” do not limit the quantity and execution order, and words such as “first” and “second” do not necessarily limit them to be different.

[0069] Before explaining the embodiments of the present application in detail, the application scenarios of the embodiments of the present application are first explained.

[0070] The robot quantity adjustment method provided in the embodiment of the present application can be applied to fields such as warehousing and logistics, and can replace manual labor to complete complex and tedious tasks in scenarios in specific areas by setting up a certain number of robots.

[0071] For example, in certain areas such as specific communities, campuses, office buildings, etc., logistics delivery personnel are not allowed to enter, making it impossible for logistics delivery personnel to enter these specific places to complete delivery tasks. In this case, the delivery of items can be achieved through multiple robots.

[0072] As an example, a certain number of robots are pre-installed within a specific area. Each of the robots includes at least one cargo compartment for storing items. Upon receiving a pickup instruction, any of the robots drives to a designated pickup location to retrieve the items to be delivered, and then transports the items to be delivered to a corresponding receiving location. Alternatively, at least one container is pre-installed within a specific area. The at least one container stores items of different types and / or quantities, and each of the at least one container has a corresponding designated pickup location. Upon receiving a pickup instruction, any of the robots drives to a pickup location of a container storing items to be delivered, retrieves the items to be delivered, and then transports the items to be delivered to a corresponding receiving location.

[0073] An embodiment of the present application proposes a method for adjusting the number of robots, which can automatically and reasonably adjust the number of robots in the target area based on the total time each robot in the target area waits to perform a delivery task within a preset time period and the total time to perform the delivery task. Therefore, when robots with a reasonable number of robots deliver items, the resource utilization rate and task completion efficiency of the robots can be better balanced and both are high.

[0074] Please refer to Figure 1 , Figure 1 This is a flowchart of a robot quantity adjustment method provided by an embodiment of the present application. This method can be applied to a master control robot within a target area, where the master control robot is connected to each of the other robots within the target area, or applied to a computer device, where the computer device is connected to each robot within the target area. The computer device can be a terminal, server, or embedded device, and the terminal can be a desktop computer or tablet computer. The following description will use the robot quantity adjustment method executed by a computer device as an example. The method includes the following steps:

[0075] Step 101: For M robots in a target area, a computer device determines a first waiting time and a first attendance time of each of the M robots within a first preset time.

[0076] It should be noted that before the computer device determines the first waiting time and the first attendance time of each of the M robots within the first preset time period, there are M robots in the target area. These M robots can be robots that are manually set in the target area based on experience, or they can be robots after the number of robots in the target area is adjusted.

[0077] Where M is a positive integer, and the target area is the delivery area of the item. For example, the target area can be a specific area within a community, campus, office building, etc.

[0078] As an example, M is the number of robots in the target area set based on experience within a specific time period, which can be hours, days, months, etc. For example, the number of robots M in the target area can be set based on the importance of the time point and the number of transaction and delivery orders at that time. For example, if there are more transaction orders between 11:00 and 15:00 each day and fewer between 20:00 and 24:00 each day, more robots can be deployed during the 11:00-15:00 period to alleviate delivery pressure, and fewer robots can be deployed during the 20:00-24:00 period to avoid wasting robot resources.

[0079] Among them, the first waiting time is the total time the corresponding robot waits to perform the delivery task within the first preset time, and the first attendance time is the total time the corresponding robot performs the delivery task within the first preset time.

[0080] As an example, "waiting to execute a delivery task" may mean that the corresponding robot is in a waiting state, and "executing a delivery task" may mean that the corresponding robot is in a searching state or a delivering state. Thus, the first waiting duration is the total duration of the corresponding robot's waiting state within the first preset duration, and the first on-duty duration is the sum of the total duration of the corresponding robot's searching state and the total duration of the robot's delivering state within the first preset duration. The waiting state indicates that the corresponding robot is waiting to go to the receiving location to search for items to be delivered, the searching state indicates that the corresponding robot is traveling to the receiving location to search for items to be delivered or receiving items to be delivered at the receiving location, and the delivering state indicates that the corresponding robot is traveling from the receiving location to the receiving location to deliver items to be delivered or distributing items to be delivered at the receiving location.

[0081] As an example, each robot's operating state can include a waiting state, a searching state, or a delivery state. For example, each robot's operating state includes at least a waiting state, a searching state, and a delivery state. Furthermore, each robot's operating state can also include a charging state, where the charging state indicates that the robot is heading to or charging at a designated charging location. The waiting state can also indicate that the robot's battery level is greater than a threshold and that the robot is waiting to head to a pickup location to search for items to be delivered.

[0082] Among them, the total time that each of the M robots waits to perform the delivery task within the first preset time period (first waiting time) and the total time to perform the delivery task (first attendance time) can reflect the task completion efficiency and the resource utilization rate of the robot in the target area.

[0083] For example, if the total time that each of the M robots waits to perform the delivery task is relatively short, then each robot can be determined as the robot for delivering items in a relatively short time within the first preset time. The number of robots waiting to perform the delivery task among the M robots within the first preset time may be small, the number of robots in the waiting state among the M robots may be small, and the number of M robots in the target area may be relatively small, resulting in the M robots being unable to complete the delivery task in time, resulting in low task completion efficiency in the target area.

[0084] For another example, if the total time for each of the M robots to perform the delivery task is relatively short, then each robot is determined to perform the delivery task only within a shorter period of time within the first preset time period. The number of robots performing delivery tasks among the M robots may be relatively small, and the number of robots in the searching state or the delivery state among the M robots may be relatively small. The number of M robots in the target area may be relatively large, resulting in some of the M robots being in a waiting state for a longer time within the first preset time period, causing a waste of robot resources and a low resource utilization rate of the robots.

[0085] The first preset duration includes one or more preset time periods, which may be hours, days, months, etc. For example, the first preset duration includes a preset time period, which may be 10 days, 20 days, or 30 days, etc. Alternatively, the first preset duration includes multiple preset time periods, which may be the 11:00-15:00 time period of each of the 20 days.

[0086] As an example, before determining the first waiting time and first attendance time of each of the M robots within a first preset time period, the computer device must first control the M robots to complete a delivery task within a target area. In the process of completing the delivery task within the target area, each of the M robots has a waiting time and a delivery task execution time. Thus, after controlling the M robots to complete the delivery task within the target area within the first preset time period, the computer device can determine the first waiting time and first attendance time of each of the M robots within the first preset time period. Of course, the computer device can also control the M robots to complete the delivery task within the target area during or after determining the first waiting time and first attendance time of each of the M robots within the first preset time period.

[0087] For example, waiting to execute a delivery task means that the corresponding robot is in a waiting state, and executing a delivery task means that the corresponding robot is in a searching state or a delivering state. Each of the M robots has a different working state in the process of completing the delivery task within the target area within a first preset time period. The computer device can determine the first waiting time and the first attendance time of each robot within the first preset time period based on the working state of each of the M robots within the first preset time period. For example, the computer device first determines the total time that each robot is in the waiting state, the total time that it is in the searching state, and the total time that it is in the delivering state within the first preset time period based on the working state of each of the M robots within the first preset time period, and then determines the total time that each robot is in the waiting state within the first preset time period as the first waiting time, and determines the sum of the total time that each robot is in the searching state and the total time that it is in the delivering state within the first preset time period as the first attendance time.

[0088] It should be noted that the specific implementation process of the computer equipment controlling the robot in the target area to complete the delivery task in the target area will be described in the following Figure 2 The details are described in the examples, and the examples of this application are not described here in detail.

[0089] Step 102: The computer device adjusts the number of robots in the target area according to the first waiting time and the first attendance time of the M robots.

[0090] Since the number M of robots in the target area may be too small or too large, the number of robots in the target area can be adjusted to be less than M or greater than M according to the first waiting time and the first attendance time of the M robots.

[0091] For example, if the number of robots among the M robots whose first waiting time is greater than the first time threshold is less than or equal to the number threshold, the first instruction is triggered, and the first instruction is used to instruct to increase the number of robots in the target area; if the number of robots among the M robots whose first waiting time is greater than the first time threshold is greater than the number threshold, the second instruction is triggered according to the first attendance time of the M robots, and the second instruction is used to instruct to reduce the number of robots in the target area.

[0092] The first duration threshold is a preset duration, and the quantity threshold is a preset value. For example, the first duration threshold can be 0 minutes, 60 minutes, or 120 minutes, and the quantity threshold can be 1, 3, or 5, etc., which are not limited in the present embodiment.

[0093] Among them, the first waiting time of each robot being greater than the first time threshold indicates that the total time the corresponding robot waits to perform the delivery task is longer, and the time the corresponding robot is in the waiting state is longer.

[0094] For ease of explanation, in the embodiment of the present application, the number of robots among the M robots whose first waiting time exceeds the first time threshold is referred to as the second number. If the second number is less than or equal to the number threshold, it indicates that only a relatively small number of the M robots were in the waiting state for a longer period within the first preset time. In this case, the number of M robots in the target area may be insufficient. Thus, if the number of robots among the M robots whose first waiting time exceeds the first time threshold is less than or equal to the number threshold, the computer device determines that the number of robots M may be insufficient and triggers the first instruction to increase the number of robots in the target area.

[0095] For example, M is 10, the first preset time is 20 days, the first time threshold is 60 minutes, the quantity threshold is 3, and the first waiting times of the 10 robots are 3 minutes, 10 minutes, 20 minutes, 15 minutes, 42 minutes, 30 minutes, 50 minutes, 20 minutes, 70 minutes, and 15 minutes respectively. The computer device determines that the number of robots among the M robots whose first waiting time is greater than the first time threshold (60 minutes) is 1, and 1 is less than the quantity threshold (3), indicating that only a few of the 10 robots have a total waiting time greater than the first time threshold, and only a few of the 10 robots have a longer waiting time. Most of the 10 robots can be determined as robots for delivering items in a shorter time. Within the first preset time (20 days), the number of robots among the 10 robots waiting to perform delivery tasks may be small, the number of robots among the 10 robots in the waiting state may be small, and the number of 10 robots may be relatively small.

[0096] As an example, the first instruction may be a control instruction for increasing the number of robots within a target area. For example, after triggering the first instruction, the computer device increases the number of robots within the target area via a storage device, where the storage device is respectively connected to at least one fourth robot. For example, after triggering the first instruction, the computer device may determine some of the at least one fourth robot respectively connected to the storage device as robots to perform delivery tasks within the target area, thereby increasing the number of robots within the target area.

[0097] As another example, the first instruction may be a prompt instruction for issuing a prompt message, or the first instruction may be an information transmission instruction for instructing the issuance of an instruction to a terminal of a relevant person, so that the relevant person increases the number of robots within the target area according to the prompt message or the instruction received by the terminal. For example, if the first instruction is a prompt instruction, the computer device triggers the first instruction and issues a prompt message, so that the relevant person can increase the number of robots within the target area according to the prompt message. The method of issuing the prompt message may include displaying the prompt message or emitting a prompt sound.

[0098] As an example, the first instruction can also be used to instruct to increase the number of robots in the target area by a first preset value. The first preset value can be 5 or 10, etc., so that the computer equipment or relevant personnel can increase the number of robots in the target area by the first preset value.

[0099] The second number being greater than the threshold indicates that a significant number of the M robots were in a waiting state for extended periods within the first preset duration. In this case, the number of M robots in the target area may be excessive. Thus, if the number of robots in the target area whose first waiting duration exceeded the first duration threshold exceeds the threshold, a second instruction is triggered based on the first attendance duration of the M robots to reduce the number of robots in the target area.

[0100] For example, M is 10, the first preset duration is 20 days, the first duration threshold is 60 minutes, the quantity threshold is 3, and the first waiting durations of the 10 robots are 70 minutes, 43 minutes, 152 minutes, 134 minutes, 74 minutes, 110 minutes, 80 minutes, 92 minutes, 70 minutes, and 30 minutes, respectively. The computer device determines that the number of robots whose first waiting duration is greater than the first duration threshold (60 minutes) among the M robots is 8, and 8 is greater than the quantity threshold (3). This indicates that the total waiting time for the delivery task of more robots among the 10 robots is greater than the duration threshold, and more robots among the 10 robots are in the waiting state for a longer time. Within the first preset duration (20 days), the number of robots waiting to perform the delivery task among the 10 robots may be large, and the 10 robots can complete the delivery task in the target area. However, since more robots among the 10 robots are in the waiting state for a longer time, the number of 10 robots may be too large.

[0101] For example, the computer device may first determine a first number, which is the number of robots among the M robots whose first attendance duration is greater than a second duration threshold. The computer device may then trigger a second instruction based on the first number, the second instruction being used to instruct the number of robots in the target area to be reduced to the first number, so that the computer device or relevant personnel can reduce the number of robots in the target area to the first number. The second duration threshold is a pre-set duration, such as 60 minutes or 120 minutes, etc., which is not limited in this embodiment of the present application.

[0102] For example, if the first on-duty duration of each of the M robots is greater than the second duration threshold, that is, the first number is M, then there may be a small number of M robots in the target area. Thus, if the number of robots in the M robots whose first waiting duration is greater than the first duration threshold is greater than the number threshold, and the first on-duty duration of each of the M robots is greater than the second duration threshold, then the computer device may trigger the first instruction.

[0103] As an example, if the first attendance duration of each of the M robots is less than or equal to the second duration threshold, that is, the first number is 0, in this case, there may be a situation where the number of M robots in the target area is too large. In this case, if the number of robots in the M robots whose first waiting duration is greater than the first duration threshold is greater than the quantity threshold, and the first attendance duration of each of the M robots is less than or equal to the second duration threshold, then the computer device can trigger a third instruction, which is used to instruct to reduce the number of robots in the target area by a second preset value. The second preset value can be 5 or 10, etc., and this embodiment of the application is not limited to this.

[0104] As an example, the second instruction may be a control instruction for reducing the number of robots in the target area. For example, after triggering the first instruction, the computer device may control the robots among the M robots whose first attendance duration is less than or equal to the second attendance duration threshold to stop working, i.e., the robots among the M robots whose first attendance duration is less than or equal to the second attendance duration threshold are eliminated, and the warehouse is connected to each of the eliminated robots, so that the robots among the M robots whose first attendance duration is greater than the second attendance duration threshold continue to complete delivery tasks within the target area, thereby reducing the number of robots in the target area from M to the first number.

[0105] As another example, the second instruction may also be a prompt instruction or an information sending instruction. The prompt instruction is used to issue a prompt message, and the information sending instruction is used to instruct to issue an instruction to the terminal of the relevant personnel, so that the relevant personnel can reduce the number of robots in the target area according to the prompt message or the instruction received by the terminal.

[0106] For ease of explanation, in the embodiment of the present application, the number of robots after the number of robots in the target area is increased is referred to as N, that is, after the number of robots in the target area is increased, the number of robots in the target area increases from M robots to N robots, where N is a positive integer and N is greater than M.

[0107] Since the number of N robots in the target area may still be too many or too few after the number of robots in the target area is increased, the computer device may, after triggering the first instruction, further determine whether the number of N robots in the target area is too many or too few, so as to adjust the number of robots in the target area based on whether the number of N robots in the target area is too many or too few. The specific implementation process of determining whether the number of N robots in the target area is too many or too few to adjust the number of robots in the target area may be: after the computer device triggers the first instruction, if the number of robots in the target area increases from M robots to N robots, then determining a second waiting time for each of the N robots within a second preset time period; if the number of robots in the N robots whose second waiting time exceeds the first time period threshold is less than or equal to a number threshold, then triggering the first instruction; if the number of robots in the N robots whose second waiting time exceeds the first time period threshold is greater than the number threshold, then determining a second attendance time for each of the N robots within the second preset time period, and triggering the second instruction based on the second attendance time of the N robots. The second preset time period is after the first preset time period.

[0108] As an example, the second preset duration includes one or more pre-set time periods, the length of the time period of the first preset duration and the length of the time period of the second preset duration may be the same or different, and the second preset duration being after the first preset duration means that the time point in the second preset duration is after the time point in the first preset duration.

[0109] For example, a computer device controls M robots within a target area to complete a delivery task within the target area within a first preset duration, and then determines a first waiting time and a first on-duty time for each of the M robots within the first preset duration. Then, if the number of robots within the M robots whose first waiting time exceeds a first duration threshold is less than or equal to a quantity threshold, a first instruction is triggered. Subsequently, after the first instruction is triggered, if the number of robots within the target area increases from M robots to N robots, the N robots within the target area are controlled to complete a delivery task within the target area within a second preset duration, and a second waiting time for each of the N robots within the second preset duration is determined.

[0110] For example, if the number of robots among the N robots whose second waiting time exceeds the first time threshold is less than or equal to the number threshold, this indicates that only a small number of the N robots were in the waiting state for a long period of time within the second preset time. In this case, after increasing the number of robots in the target area, the number of N robots in the target area may be relatively small. Thus, if the number of robots among the N robots whose second waiting time exceeds the first time threshold is less than or equal to the number threshold, the first instruction is triggered to increase the number of robots in the target area again.

[0111] It should be noted that after the computer device triggers the first instruction, if the number of robots in the target area increases again from N robots, the number of robots in the target area after the increase may still be too many or too few. In this case, the computer device can determine whether the number of robots in the target area after the increase from N robots is too many or too few, so as to adjust the number of robots in the target area. The specific implementation process of determining whether the number of robots in the target area after the increase from N robots is too many or too few, and adjusting the number of robots in the target area, is similar to the implementation process of determining whether the number of robots in the target area is too many or too few, and will not be repeated here.

[0112] As an example, if the number of N robots whose second waiting time exceeds the first time threshold is greater than the number threshold, this indicates that a greater number of the N robots were in a waiting state for a longer period within the second preset time. That is, after increasing the number of robots in the target area, a greater number of the N robots in the target area may be waiting to perform delivery tasks, and the number of N robots may be excessive. Thus, if the number of N robots whose second waiting time exceeds the first time threshold is greater than the number threshold, a second attendance time for each of the N robots within the second preset time is determined, and a fourth instruction is triggered based on the second attendance time of the N robots. The fourth instruction is used to instruct a reduction in the number of robots in the target area.

[0113] For example, the computer device first determines a third number, which is the number of robots among N robots whose second attendance duration is greater than the second duration threshold, and then triggers a fourth instruction based on the third number. The fourth instruction is used to instruct the number of robots in the target area to be reduced to the third number.

[0114] In an embodiment of the present application, the first waiting time and first attendance time of each of the M robots in a target area within a first preset time period can be first determined, and then the number of robots in the target area can be adjusted based on the first waiting time and first attendance time of the M robots. Where M is a positive integer, the first waiting time is the total time the corresponding robot waits to perform a delivery task within the first preset time period, and the first attendance time is the total time the corresponding robot performs a delivery task within the first preset time period. In this way, the number of robots in the target area can be automatically adjusted based on the total time each robot waits to perform a delivery task within the preset time period and the total time each robot performs a delivery task. Because the first waiting time and first attendance time can reflect the task completion efficiency and the resource utilization rate of the robots within the target area, the number of robots in the target area automatically adjusted based on the first waiting time and first attendance time of each robot is more reasonable, thereby achieving a good balance between the resource utilization rate of the robots and the task completion efficiency within the target area, and both are high.

[0115] It should be noted that in the above Figure 1 In the embodiment, before or after step 101, before or after step 102, or during the execution of step 101 or step 102, the computer device can control the robot in the target area to complete the delivery task in the target area. Figure 1 The robots before the robot quantity adjustment in the embodiment, such as the M robots before the adjustment, can also be the robots Figure 1 The robots after the number of robots is adjusted in the embodiment, such as the adjusted N robots, which is not limited in the embodiment of the present application.

[0116] For example, a computer device may control a robot in a target area to complete a delivery task in the target area by executing the following item delivery method.

[0117] Please refer to Figure 2 , Figure 2 This is a flow chart of an item delivery method provided by an embodiment of the present application. This method can be applied to a master robot within a target area, where the master robot is connected to each of the other robots within the target area, or applied to a computer device, where the computer device is connected to each of the robots within the target area. The computer device can be a terminal, server, or embedded device, and the terminal can be a desktop computer or tablet computer. The following description will use the example of a computer device executing the item delivery method. The method includes the following steps:

[0118] In step 201 , for a target item to be delivered, a computer device determines a target delivery location, a target receiving location, and a target number of delivery warehouses for the target item.

[0119] Among them, each robot in the target area includes at least one warehouse for storing items, the types of items stored in at least one warehouse can be the same or different, and the storage capacity of at least one warehouse can be the same or different. The embodiment of the present application does not limit the warehouse.

[0120] Among them, the target item may include one or more items, the target receiving location is the location where the robot obtains the target item, the target receiving location is the delivery location (address) corresponding to the target item, and the target delivery warehouse quantity is the number of warehouses required for the robot to store the target item.

[0121] For example, a computer device can generate a transaction delivery order, and determine the target delivery location, target pick-up location, and target delivery warehouse quantity based on the content of the transaction delivery order and the items stored in at least one container. The computer device and the robot in the target area are respectively connected to at least one container, the at least one container is used to store items, and at least one container stores items of different types and / or different quantities. Each container in the at least one container is correspondingly provided with a designated pick-up location. The content of the transaction delivery order includes an order identifier, a target delivery location, and an item identifier and item quantity of the target item. The order identifier is used to uniquely identify the transaction delivery order and can be an order number, etc. The item identifier is used to uniquely identify the item and can be an item name or item number, etc. This embodiment of the present application does not limit this.

[0122] As an example, a computer device can determine a target container from at least one container based on the item identification, item quantity, and items stored in at least one container in a transaction delivery order, and determine the receiving location corresponding to the target container as the target receiving location. The target container stores the target items, and the target container can include one or more containers.

[0123] For example, the computer device determines whether there is a container storing the target number of items in at least one container. If so, the container storing the target number of items is determined as the target container. If not, the container storing the largest number of items is first determined as the first target container from at least one container, and then the difference between the number of items and the number of target items in the first target container is determined as a fourth number. Based on the fourth number, a second target container is determined from other containers in at least one container except the first target container. The second target container is a container storing the target item and the number of target items stored is greater than or equal to the fourth number.

[0124] As an example, the computer device can determine the target number of delivery bins based on the item identifiers and item quantities in the transaction delivery order, or it can determine the target number of delivery bins based on the item identifiers, item quantities, target item types, and the relationship between these types. For example, if the target items are a dozen eggs and three bottles of cola, since the target items include different types of goods, cola may cause the eggs to break, i.e., cola and eggs have a mutually exclusive relationship, and the number of target items is large, the computer device can determine the target number of delivery bins to be two, meaning that the robot needs to have two bins to store the cola and eggs, respectively.

[0125] For example, a user can select the target item and quantity on the item ordering interface displayed on the terminal, triggering a payment request. The payment request carries the item ID and quantity of the selected target item. The computer device receives the payment request, generates a payment order based on the item ID and quantity, and sends the payment order to the terminal. The terminal receives the payment order and displays the payment interface. The user pays the transaction amount on the payment interface, triggering a payment completion instruction. The terminal detects the payment completion instruction and sends the payment completion instruction to the computer device. The computer device receives the payment completion instruction, generates a transaction delivery order, and sends the transaction delivery order to the terminal.

[0126] As an example, a transaction delivery order may also include the recipient's contact information and / or a first pickup code. The first pickup code is used for authentication between the robot, the container, and the recipient, and is associated with the order identifier. After determining a target container from at least one container, the computer device may also send the first pickup code and order identifier to the target container, and / or send the first pickup code and order identifier to the recipient based on the recipient's contact information.

[0127] For example, the computer device can also receive delivery requests sent by the terminal and generate a transaction delivery order based on the delivery request. The delivery request contains the target delivery location, target pickup location, and target number of delivery warehouses. For example, if the user is a logistics personnel, the terminal can detect the delivery operation performed by the logistics personnel and trigger the delivery request. The delivery operation can be a click operation, a press operation, a voice operation, or a gesture operation.

[0128] As an example, the delivery request also carries a first inventory code, which is used for verification between the robot and the terminal, and is associated with the order identifier of the transaction delivery order.

[0129] In step 202, the computer device determines the target robot for delivering the target item from the robots in the target area based on the number of target delivery warehouses, the working status of each robot in the target area, and the number of free warehouses, and determines the target warehouse for storing the target item from the free warehouses of the target robots.

[0130] The working state of each robot includes at least a waiting state, a searching state and a delivery state, and each robot in the target area includes at least one warehouse for storing items.

[0131] As an example, the warehouse status of each warehouse includes an idle state, a locked state and an occupied state. The idle state indicates that the corresponding warehouse has no items stored and is not locked to store items to be delivered. The locked state indicates that the corresponding warehouse is locked to store items to be delivered. The occupied state indicates that items have been stored in the corresponding warehouse. An idle warehouse refers to a warehouse in the corresponding robot that is in an idle state.

[0132] For example, the computer device can prioritize determining the target robot from the robots in the target area that are in a searching state, thereby rationally utilizing robot resources and improving delivery efficiency. For example, the computer device determines whether there is at least one first robot in the target area that is in a searching state and has a number of free bins greater than or equal to the target number of delivery bins; if there is at least one first robot in the target area that is in a searching state and has a number of free bins greater than or equal to the target number of delivery bins, the target robot is determined from the at least one first robot; if there is no at least one first robot in the target area that is in a searching state and has a number of free bins greater than or equal to the target number of delivery bins, the computer device determines from the robots in the target area that is in a waiting state and has a number of free bins greater than or equal to the target number of delivery bins, and determines the target robot from the at least one second robot.

[0133] As an example, the computer device may determine a target robot from the at least one first robot based on a target pickup location, the location of each of the at least one first robot, a pending pickup location, and the number of available cargo bins. Each of the at least one first robot is currently traveling to another pending pickup location to search for other items to be delivered, and the pending pickup location is a pickup location corresponding to the other items to be delivered when each first robot is in the searching state.

[0134] For example, the computer device first identifies at least one third robot from at least one first robot whose target pickup location is between the first robot's position and the pickup location to be reached, and then determines the third robot with the fewest available bins among the at least one third robot as the target robot. By prioritizing the first robot in a searching state and with its target pickup location between the first robot's position and the pickup location to be reached as the target robot, the target robot can search for or retrieve multiple items to be delivered during a single movement, thereby rationalizing the use of robot resources and improving delivery efficiency. Furthermore, by prioritizing the first robot with the fewest available bins as the target robot, all bins of the first robot with the fewest available bins can be prioritized for storing items, thereby enabling the first robot with the fewest available bins to deliver items as soon as possible, further improving delivery efficiency.

[0135] As an example, if there is no at least one first robot in the target area that is in a searching state and whose number of free cargo bins is greater than or equal to the target number of delivery warehouses, the computer device may first determine whether there is a robot in the target area that is in a waiting state and whose number of free cargo bins is greater than or equal to the target number of delivery warehouses; if so, then determine from the robots in the target area at least one second robot that is in a waiting state and whose number of free cargo bins is greater than or equal to the target number of delivery warehouses, and determine the target robot from the at least one second robot; if not, then perform the step of determining whether there is at least one first robot in the target area that is in a searching state and whose number of free cargo bins is greater than or equal to the target number of delivery warehouses again after a third preset time period. The third preset time period is a pre-set time period, such as 5 minutes or 10 minutes, etc. The embodiment of the present application does not limit the third preset time period.

[0136] For example, the computer device determines the second robot with the shortest target state duration among at least one second robot as the target robot, where the target state duration is the duration after the corresponding robot's working state switches from the delivery state to the waiting state. The computer device determines that after the robot in the delivery state has delivered the items to be delivered at the receiving location, or after the items to be delivered are delivered at the receiving location and the remaining power is greater than a power threshold, the robot's working state switches from the delivery state to the waiting state. In this way, the computer device prioritizes robots that have completed delivery tasks, or robots that have completed delivery tasks and whose power is greater than the power threshold, to be re-determined as robots performing delivery tasks. This allows for the rational use of robot resources, increases the duration of the robot's delivery task, and improves the robot's delivery efficiency within a preset time period. The power threshold is a pre-set percentage threshold of the robot's remaining power, such as 30% or 20%. The present embodiment of the application does not limit the power threshold.

[0137] For example, if the computer device determines that there is no robot in the target area that is in a waiting state and the number of free warehouses is greater than or equal to the target number of delivery warehouses, that is, it determines that there is no target robot in the target area that can deliver the target item, then the computer device is in a waiting state for a third preset time period. After waiting for the third preset time period, the computer device continues to determine whether there is at least one first robot in the target area that is in a searching state and the number of free warehouses is greater than or equal to the target number of delivery warehouses.

[0138] As an example, after the computer device determines the target warehouse for storing the target item from the target robot's available warehouses, it also switches the warehouse state of the target warehouse from an idle state to a locked state to prevent the computer device from identifying the target warehouse as a warehouse for storing other items to be delivered. The warehouse identifier of the target warehouse is associated with the order identifier, or the warehouse identifier of the target warehouse is also associated with the item identifier or the item quantity, so that the target item corresponding to the order identifier is stored in the target warehouse of the target robot, and the warehouse identifier is used to uniquely identify the robot's warehouse.

[0139] In step 203, the computer device controls the target robot to go to the target receiving location to search for the target item.

[0140] For example, a computer device can send a pickup instruction to a target robot, switching the robot's operating state from a waiting state to a searching state. The pickup instruction carries the target pickup location, item ID, and item quantity. The target robot then receives the pickup instruction and, based on the item ID and item quantity, moves to the target pickup location to retrieve the target item.

[0141] For example, each robot in the target area includes an intelligent manipulator. The target robot can use the intelligent manipulator to obtain the target item from the target container corresponding to the target receiving position at the target receiving position and store the target item in the target warehouse.

[0142] As an example, a pickup instruction also carries a first pickup code and an order ID. Upon receiving the pickup instruction, the target robot proceeds to the target pickup location based on the item ID and quantity. From the target pickup location, the robot then sends a pickup request to the target container based on the first pickup code and order ID. The pickup request carries a second pickup code and order ID. Upon receiving the pickup request, if the second pickup code in the pickup request matches the first pickup code corresponding to the order ID, sent by a computer device and previously received by the target container, the target container removes the target item from its delivery port. The target robot then uses its intelligent robotic arm to retrieve the target item from the delivery port and deposit it into the target warehouse.

[0143] As an example, the receiving instruction also carries the warehouse identification of the target warehouse. The target robot uses the intelligent manipulator to obtain the target items from the shipping port and stores them in the target warehouse corresponding to the warehouse identification.

[0144] As an example, the receiving instruction may also carry an order identifier and the first inventory code in the delivery request sent by the computer device receiving terminal. The target robot also receives the inventory instruction at the target receiving location. The inventory instruction carries the second inventory code and the order identifier. If the second inventory code matches the first inventory code, the target warehouse corresponding to the order identifier is opened so that the user can store the target item directly in the target warehouse. The inventory instruction may be sent by a computer device or terminal, or may be triggered by a user, and this embodiment of the present application does not limit this. For example, the terminal detects an inventory operation triggered by a user and sends an inventory request to the computer device. The inventory request carries the second inventory code and the order identifier. The computer device receives the inventory request, determines the corresponding target robot based on the order identifier, and sends an inventory instruction to the target robot.

[0145] As an example, after the computer device determines the target cargo warehouse for storing the target item from the target robot's free cargo warehouse, it also determines whether the target robot's receiving location only includes the target receiving location; if the target robot's receiving location only includes the target receiving location, the computer device can also first perform path planning based on the target robot's position and the target receiving location to obtain a first target path, and then send a receiving instruction to the target robot, the receiving instruction also carries the first target path, so that after the target robot receives the receiving instruction sent by the computer device, it goes to the target receiving location according to the first target path; if the target robot's receiving location includes not only the target receiving location but also the receiving location to be received, the computer device can perform path planning based on the target robot's position, the target receiving location and the receiving location to be received to obtain a second target path, and then send a receiving instruction to the target robot, the receiving instruction also carries the second target path, so that after the target robot receives the receiving instruction sent by the computer device, it goes to the target receiving location and the receiving location to be received according to the second target path, so as to achieve one path to obtain all items, so that the robot resources can be reasonably utilized and the delivery efficiency can be improved.

[0146] For example, if the target robot is a robot determined from at least one first robot, the receiving location that the target robot goes to includes not only the target receiving location, but also the receiving location to be gone to. If the target robot is a robot determined from at least one second robot, the receiving location that the target robot goes to only includes the target receiving location.

[0147] As an example, if the computer device determines that the target warehouse stores the target item, it switches the warehouse status of the target warehouse from a locked state to an occupied state. For example, after the target robot deposits the target item into the target warehouse using an intelligent manipulator and the intelligent manipulator closes the target warehouse, or after the user deposits the target item into the target warehouse and manually closes the target warehouse, the target robot detects that the target warehouse is closed and sends a completed receipt response to the computer device. The completed receipt response indicates that the target item is stored in the target warehouse. The computer device then receives the completed receipt response and determines that the target item is stored in the target warehouse.

[0148] As an example, if the computer device determines that the target warehouse stores the target item, it also determines whether all the warehouses of the target robot store items; if all the warehouses of the target robot store items, the working state of the target robot is switched from the searching state to the delivering state, and the target robot is controlled to deliver the target item, or to deliver the target item and other items to be delivered; if all the warehouses of the target robot do not store all the items, and the receiving location to be gone to includes the receiving location to be gone to, that is, there is a receiving location to be gone to, then the target robot is controlled to go to the receiving location to be gone to search for other items to be delivered, and the working state of the target robot remains in the searching state; if all the warehouses of the target robot do not store all the items If the target robot is not sure whether the target robot is delivering the target item, the receiving location it is heading to does not include the receiving location to be headed to, that is, there is no receiving location to be headed to, and within the fourth preset time period, the target robot is determined to be a robot delivering other items to be delivered, then the target robot is controlled to go to the receiving location corresponding to the other items to be delivered to search for the items to be delivered, and the target robot's working state remains in the searching state; if all the warehouses of the target robot do not store all the items, there is no receiving location to be headed to, and within the fourth preset time period, the target robot's working state is switched from the searching state to the delivering state, and the target robot is controlled to deliver the target item, or to deliver the target item and other items to be delivered. The fourth preset time period is a pre-set time period, such as 5 minutes or 10 minutes, etc., and the embodiment of the present application does not limit the fourth preset time period.

[0149] For example, the computer device can determine whether all cargo compartments of the target robot store items and whether the target robot has a location to receive items based on the cargo compartment status of at least one cargo compartment of the target robot. If the cargo compartment status of at least one cargo compartment of the target robot is all occupied, it is determined that all cargo compartments of the target robot store items and there is no (no) location to receive items; if at least one cargo compartment of the target robot has a locked cargo compartment, it is determined that not all cargo compartments of the target robot store items and there is a location to receive items; if at least one cargo compartment of the target robot has an occupied or idle cargo compartment status, it is determined that not all cargo compartments of the target robot store items and there is no location to receive items.

[0150] In step 204 , when the target warehouse stores the target item, the computer device controls the target robot to move from the target receiving location to the target delivery location to deliver the target item.

[0151] The situation where the target warehouse stores the target item refers to the computer device determining that the target warehouse stores the target item.

[0152] For example, if the target item is stored in the target warehouse, the computer device can send a delivery instruction to the target robot, switching the target robot's working state from the search state to the delivery state. The delivery instruction includes the target delivery location. The target robot then receives the delivery instruction and travels from the target delivery location to the target delivery location to deliver the target item.

[0153] As an example, if the computer device determines that all of the target robot's cargo compartments store items, the computer device sends a delivery instruction to the target robot, switching the target robot's operating state from a search state to a delivery state. Alternatively, if the computer device determines that none of the target robot's cargo compartments store items, and there are no pickup locations to be reached, and the target robot has not been identified as a robot delivering other items to be delivered within a fourth preset time period, the computer device sends a delivery instruction to the target robot, switching the target robot's operating state from a search state to a delivery state.

[0154] For example, a delivery instruction may also include a pickup location to be delivered. After receiving the delivery instruction, the target robot can then proceed from the target pickup location to the target pickup location to deliver the target item, and to the pickup location to be delivered to deliver other items to be delivered. The pickup location to be delivered is the delivery location corresponding to the other items to be delivered when the target robot is in the delivery state.

[0155] As an example, the delivery instruction also carries a first self-pickup code and an order identifier. After the target robot receives the delivery instruction and travels from the target pickup location to the target delivery location, it also receives a first pickup request at the target delivery location. The first pickup request carries a third self-pickup code and an order identifier. If the third self-pickup code matches the first self-pickup code, the target warehouse corresponding to the order identifier is opened so that the user can obtain the target item from the target warehouse. The first pickup request can be sent by a computer device or a terminal, or triggered by a user. This embodiment of the present application does not limit this. For example, the terminal detects the first pickup operation triggered by the user and sends a first pickup request to the computer device. The first pickup request carries a third self-pickup code and an order identifier. The computer device receives the first pickup request, determines the corresponding target robot according to the order identifier, and sends the first pickup request to the target robot.

[0156] As an example, a delivery instruction may also carry an order identifier and the first inventory code in the delivery request sent by the computer device receiving terminal. After the target robot receives the delivery instruction and travels from the target pickup location to the target delivery location, it also receives a second pickup request at the target delivery location. The second pickup request carries a third inventory code and the order identifier. If the third inventory code matches the first inventory code, the target warehouse corresponding to the order identifier is opened, allowing the user to retrieve the target item from the target warehouse. The second pickup request can be sent by the computer device or terminal, or triggered by the user, and this is not limited in this embodiment of the application.

[0157] For example, after the target robot opens the target warehouse corresponding to the order ID, it can also use the intelligent robotic arm to store the target item in a preset locker, making it easier for the user to obtain the target item through the locker.

[0158] As an example, after the target robot opens the target warehouse corresponding to the order identifier, if it detects that the target warehouse is closed, it sends a delivery completion response to the computer device, and the delivery completion response indicates that the target robot has completed the task of delivering the target item. The computer device then receives the delivery completion response sent by the target robot and determines whether the target robot has other items to be delivered, that is, whether there are other receiving locations to be gone to; if the target robot has a receiving location to be gone to, the target robot is controlled to go from the target receiving location to the receiving location to deliver other items to be delivered, and the state of the target robot remains in the delivery state; if the target robot does not have a receiving location to be gone to, the working state of the target robot is switched from the delivery state to the waiting state, and the waiting state indicates that the corresponding robot is waiting to go to the receiving location to find items to be delivered.

[0159] Alternatively, if the target robot does not have a pickup location to go to, the computer device may first determine the target robot's remaining battery life; if the target robot's remaining battery life is greater than a battery threshold, the target robot's operating state is switched from a delivery state to a waiting state; if the target robot's remaining battery life is less than or equal to the battery threshold, the target robot is controlled to go to a designated charging location for charging, switching the target robot's operating state from a delivery state to a charging state so that the target robot can charge at the designated charging location. In this case, the waiting state indicates that the corresponding robot's battery life is greater than the battery threshold and is waiting to go to the pickup location to search for items to be delivered.

[0160] As an example, if the computer device determines that the target robot is fully charged, or the remaining power of the target robot after charging is greater than the power threshold, there is no robot in the waiting state or the searching state in the target area, and the computer device is in the waiting state for the third preset time, then the working state of the target robot is switched from the charging state to the waiting state, so as to avoid the lack of robots that can deliver items in the target area for a long time and improve the user experience.

[0161] It should be noted that, through the above steps 201 to 204, the computer device can control the robots in the target area to complete the delivery task in the target area. Since each robot has a different working state in the process of completing the delivery task, and has a waiting time and a time to execute the delivery task, the computer device can determine the first waiting time and the first attendance time of each robot within the first preset time according to the working state of each robot in the M robots within the first preset time.

[0162] In an embodiment of the present application, for a target item to be delivered, the computer device first determines the target delivery location, target receiving location, and target number of delivery warehouses for the target item. Based on the target number of delivery warehouses, the working status of each robot in the target area, and the number of available warehouses, the computer device determines a target robot for delivering the target item from the robots in the target area. The computer device then controls the target robot to search for the target item at the target receiving location. If the target item is stored in the target warehouse, the computer device controls the target robot to travel from the target receiving location to the target delivery location to deliver the target item. In this way, the computer device can control the robot to complete the delivery task within the target area.

[0163] Please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of a robot quantity adjustment device provided in an embodiment of the present application. The robot quantity adjustment device can be implemented as part or all of a computer device by software, hardware, or a combination of both. The computer device can be as follows Figure 4 Computer equipment shown. Figure 3 The robot quantity adjustment device includes: a first determination module 301 and an adjustment module 302.

[0164] The first determining module 301 is configured to determine, for each of the M robots in the target area, a first waiting time and a first attendance time within a first preset time period, where M is a positive integer, the first waiting time is the total time the corresponding robot waits to perform a delivery task within the first preset time period, and the first attendance time is the total time the corresponding robot performs a delivery task within the first preset time period.

[0165] The adjustment module 302 is configured to adjust the number of robots in the target area according to the first waiting time and the first attendance time of the M robots.

[0166] As an example, the adjustment module 302 is further configured to trigger a first instruction to increase the number of robots in the target area if the number of robots among the M robots whose first waiting time is greater than the first time threshold is less than or equal to a number threshold.

[0167] If the number of robots among the M robots whose first waiting time is greater than the first time threshold is greater than the number threshold, the second instruction is triggered according to the first attendance time of the M robots, and the second instruction is used to instruct to reduce the number of robots in the target area.

[0168] As an example, the adjustment module 302 is further configured to determine a first number, where the first number is the number of robots among the M robots whose first attendance duration is greater than a second duration threshold;

[0169] A second instruction is triggered according to the first number, and the second instruction is used to instruct to reduce the number of robots in the target area to the first number.

[0170] As an example, the robot quantity adjustment device further includes a second determination module, a first trigger module and a second trigger module.

[0171] The second determining module is configured to determine a second waiting time for each of the N robots within a second preset time period if the number of robots in the target area increases from M robots to N robots, where N is a positive integer and greater than M, and the second preset time period is after the first preset time period;

[0172] The first triggering module is configured to trigger the first instruction if the number of robots among the N robots whose second waiting time is greater than the first waiting time threshold is less than or equal to a number threshold;

[0173] The second trigger module is used to determine the second attendance duration of each of the N robots within the second preset duration if the number of robots among the N robots whose second waiting duration is greater than the first duration threshold is greater than the number threshold, and trigger the second instruction according to the second attendance duration of the N robots.

[0174] As an example, the robot quantity adjustment device further includes a third determination module, a fourth determination module, a first control module, and a second control module:

[0175] The third determination module is used to determine the target delivery location, target receiving location and target delivery warehouse quantity of the target item to be delivered;

[0176] The fourth determination module is configured to determine a target robot for delivering the target item from the robots in the target area based on the target number of delivery bins, the operating status of each robot in the target area, and the number of available bins, and to determine a target bin for storing the target item from the available bins of the target robots, wherein each robot in the target area includes at least one bin for storing an item.

[0177] The first control module is used to control the target robot to go to the target receiving location to search for the target item;

[0178] The second control module is used to control the target robot to deliver the target item from the target receiving location to the target delivery location when the target item is stored in the target warehouse.

[0179] As an example, the warehouse status of each warehouse in the at least one warehouse includes an idle state, a locked state, and an occupied state, and the idle warehouse is a warehouse in the corresponding robot that is in an idle state; the robot quantity adjustment device further includes a first switching module and a second switching module:

[0180] The first switching module is used to switch the warehouse state of the target warehouse from the idle state to the locked state;

[0181] The second switching module is used to switch the warehouse state of the target warehouse from a locked state to an occupied state.

[0182] As an example, the working state of each robot includes at least a waiting state, a searching state, and a delivery state. The waiting state indicates that the corresponding robot is waiting to go to the receiving location to search for items to be delivered. The searching state indicates that the corresponding robot is going to the receiving location to search for items to be delivered or receiving items to be delivered at the receiving location. The delivery state indicates that the corresponding robot is going from the receiving location to the receiving location to deliver items to be delivered or is distributing items to be delivered at the receiving location.

[0183] The fourth determining module is further configured to determine a target robot from the at least one first robot if there is at least one first robot in a searching state and the number of free cargo bins of the first robot is greater than or equal to the number of target delivery cargo bins among the robots in the target area;

[0184] If there is no at least one first robot in the target area that is in a searching state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses, then at least one second robot in a waiting state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses is determined from the robots in the target area, and the target robot is determined from the at least one second robot.

[0185] As an example, the fourth determination module is also used to determine the second robot with the shortest target state duration among at least one second robot as the target robot, and the target state duration is the duration after the working state of the corresponding robot switches from the delivery state to the waiting state.

[0186] It should be noted that the robot quantity adjustment device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0187] The functional units and modules in the above embodiments may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The above integrated units may be implemented in the form of hardware or software functional units. In addition, the specific names of the functional units and modules are only for the purpose of distinguishing them from each other and are not intended to limit the scope of protection of the embodiments of this application.

[0188] The robot quantity adjustment device and the robot quantity adjustment method provided in the above embodiments belong to the same concept. The specific working process of the units and modules in the above embodiments and the technical effects brought about can be found in the method embodiment part and will not be repeated here.

[0189] Please refer to Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. Figure 4 As shown, the computer device includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, the steps of the robot quantity adjustment method in the above embodiment are implemented.

[0190] The computer device may be the computer device in the above-mentioned embodiment 1 or embodiment 2. The computer device may be a near-eye display device, or a desktop computer, a portable computer, a network server, a PDA, a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer device. Those skilled in the art will understand that Figure 4 This is merely an example of a computer device and does not constitute a limitation on the computer device. The computer device may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0191] The processor 401 may be a central processing unit (CPU), or may be another general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0192] In some embodiments, the memory 402 may be an on-chip memory or an off-chip memory of the computer device, such as a cache memory, SRAM (Static Random-Access Memory), DRAM (Dynamic Static Random-Access Memory), or a floppy disk. In other embodiments, the memory 402 may also be a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash memory card, or the like equipped on the computer device. Furthermore, the memory 402 may include both an on-chip memory of the computer device, an off-chip memory internal storage unit, and an external storage device. The memory 402 is used to store an operating system, application programs, a boot loader, data, and other programs. The memory 402 may also be used to temporarily store data that has been output or is about to be output.

[0193] An embodiment of the present application also provides a computer device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor implements the steps of any of the above-mentioned method embodiments when executing the computer program.

[0194] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0195] An embodiment of the present application provides a computer program product, which, when executed on a computer, enables the computer to execute the steps in the above-mentioned various method embodiments.

[0196] If the integrated unit is implemented as a software functional unit and sold or used as a standalone product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the processes in the above-mentioned method embodiments by using a computer program to instruct the relevant hardware. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can at least include: any entity or device capable of carrying the computer program code to the camera / terminal device, recording medium, computer memory, ROM (Read-Only Memory), RAM (Random Access Memory), CD-ROM (Compact Disc Read-Only Memory), magnetic tape, floppy disk, and optical data storage device. The computer-readable storage medium mentioned in the present application can be a non-volatile storage medium, in other words, a non-transitory storage medium.

[0197] It should be understood that all or part of the steps for implementing the above embodiments may be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the steps may be implemented in the form of a computer program product. The computer program product may include one or more computer instructions. The computer instructions may be stored in the above-mentioned computer-readable storage medium.

[0198] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for adjusting the number of robots, characterized in that: The method comprises: For M robots in a target area, determine a first waiting time and a first attendance time for each of the M robots within a first preset time period, where M is a positive integer, the first waiting time is the total time the corresponding robot waits to perform a delivery task within the first preset time period, and the first attendance time is the total time the corresponding robot performs a delivery task within the first preset time period; If the number of robots among the M robots whose first waiting time is greater than the first time threshold is less than or equal to the number threshold, triggering a first instruction, wherein the first instruction is used to instruct to increase the number of robots in the target area; If the number of robots among the M robots whose first waiting time is greater than the first time threshold is greater than the number threshold, a second instruction is triggered according to the first attendance time of the M robots, and the second instruction is used to instruct to reduce the number of robots in the target area.

2. The method according to claim 1, wherein The triggering of the second instruction according to the first attendance durations of the M robots includes: Determine a first number, where the first number is the number of robots among the M robots whose first attendance duration is greater than a second attendance threshold; The second instruction is triggered according to the first number, and the second instruction is used to instruct to reduce the number of robots in the target area to the first number.

3. The method according to claim 1, wherein After triggering the first instruction, the method further includes: If the number of robots in the target area increases from the M robots to N robots, determining a second waiting time within a second preset time for each of the N robots, where N is a positive integer and N is greater than M, and the second preset time is after the first preset time; If the number of robots among the N robots whose second waiting time is longer than the first waiting time threshold is less than or equal to the number threshold, triggering the first instruction; If the number of robots among the N robots whose second waiting time is greater than the first time threshold is greater than the number threshold, the second attendance time of each of the N robots within the second preset time is determined, and the second instruction is triggered according to the second attendance time of the N robots.

4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: For the target items to be delivered, determine the target delivery location, target pickup location, and target delivery warehouse quantity of the target items; Determining a target robot for delivering the target item from the robots in the target area based on the target number of delivery bins, the working status of each robot in the target area, and the number of free bins, and determining a target bin for storing the target item from the free bins of the target robots, wherein each robot in the target area includes at least one bin for storing items; Controlling the target robot to go to the target receiving location to search for the target item; In a case where the target warehouse stores the target item, the target robot is controlled to move from the target receiving position to the target delivery position to deliver the target item.

5. The method according to claim 4, wherein The cargo state of each cargo bin in the at least one cargo bin includes an idle state, a locked state, and an occupied state, and the idle cargo bin is a cargo bin in the corresponding robot that is in the idle state; After determining the target cargo bin for storing the target object from the free cargo bins of the target robot, the method further includes: Switching the cargo hold state of the target cargo hold from the idle state to the locked state; Before controlling the target robot to move from the target receiving location to the target delivery location to deliver the target item, the method further includes: The warehouse state of the target warehouse is switched from the locked state to the occupied state.

6. The method according to claim 4, wherein The working state of each robot includes at least a waiting state, a searching state, and a delivery state, wherein the waiting state indicates that the corresponding robot is waiting to go to the receiving location to search for items to be delivered, the searching state indicates that the corresponding robot is going to the receiving location to search for items to be delivered or receiving items to be delivered at the receiving location, and the delivery state indicates that the corresponding robot is going from the receiving location to the receiving location to deliver items to be delivered or issuing items to be delivered at the receiving location; The step of determining a target robot for delivering the target item from the robots in the target area according to the target number of delivery bins, the working status of each robot in the target area, and the number of free bins includes: If there is at least one first robot in the target area that is in the search state and has a number of free cargo bins greater than or equal to the target delivery cargo bin number, determining the target robot from the at least one first robot; If there is no at least one first robot in the target area that is in the searching state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses, then at least one second robot in the waiting state and whose number of free warehouses is greater than or equal to the target number of delivery warehouses is determined from the robots in the target area, and the target robot is determined from the at least one second robot.

7. The method according to claim 6, wherein The determining the target robot from the at least one second robot comprises: The second robot with the shortest target state duration among the at least one second robot is determined as the target robot, where the target state duration is the duration after the working state of the corresponding robot switches from the delivery state to the waiting state.

8. A robot quantity adjustment device, characterized in that: The device comprises: a first determination module configured to determine, for M robots in a target area, a first waiting time and a first attendance time of each of the M robots within a first preset time period, where M is a positive integer, the first waiting time being the total time the corresponding robot waits to perform a delivery task within the first preset time period, and the first attendance time being the total time the corresponding robot performs a delivery task within the first preset time period; An adjustment module is configured to trigger a first instruction if the number of robots among the M robots whose first waiting time is greater than a first time threshold is less than or equal to a number threshold, and the first instruction is used to instruct an increase in the number of robots in the target area; and to trigger a second instruction according to the first attendance time of the M robots if the number of robots among the M robots whose first waiting time is greater than the first time threshold is greater than the number threshold, and the second instruction is used to instruct a reduction in the number of robots in the target area.

9. A computer device, characterized in that: The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the method according to any one of claims 1 to 7 when executed by the processor.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

Images