Intelligent scheduling method and system for autonomous mobile robot

Abstract

The invention provides an intelligent scheduling method and system for autonomous mobile robots, and the method comprises the steps: constructing a scheduling queue of the autonomous mobile robots, a plurality of loading queues corresponding to loading stations, and a plurality of unloading queues corresponding to unloading stations, and enabling any one autonomous mobile robot to enter an idle state, recalculating the carrying capacity of the autonomous mobile robot, adding the autonomous mobile robot in an idle state to the scheduling queue, and reading a list of articles to be loaded corresponding to each loading site, according to the carrying capacity of each autonomous mobile robot in the scheduling queue, to-be-loaded articles are matched for the autonomous mobile robots in the scheduling queue in the to-be-loaded article list; and the autonomous mobile robot is moved from the scheduling queue to the loading queue corresponding to the loading station where the matched to-be-loaded object is located, and it can be guaranteed that the autonomous mobile robot stably and efficiently completes the transportation task.

Description

Technical Field

[0001] The present invention relates to the technical field of autonomous mobile robots, and in particular to an intelligent scheduling method and system for autonomous mobile robots. Background Art

[0002] AMR (Autonomous Mobile Robot) is a robot with autonomous mobility and decision-making capabilities. It can autonomously navigate, plan paths, and perform specific tasks in a specified environment without human intervention. These features of AMR have made it widely used in industrial manufacturing, logistics warehousing, agricultural production, and medical and health care, especially in the short-distance load-bearing transportation of a large number of items, which greatly reduces the dependence of transportation on manpower and greatly improves transportation efficiency.

[0003] In order to make the autonomous mobile robot have flexible autonomous mobility, it usually uses a built-in power battery to provide power for autonomous mobility. When the power battery is fully charged, it can usually provide very strong driving ability. However, due to the loss of its battery and the change of ambient temperature and other factors, the driving ability it can provide also decreases. This situation will be more obvious when the autonomous mobile robot is loaded. For example, in the field of industrial manufacturing, the workpieces or auxiliary equipment that need to be transported are often heavy items. In a production workshop or storage environment, when there are a large number of heavy objects to be transported, it is more common to use multiple autonomous mobile robots for cluster transportation. Under the influence of factors such as battery loss and ambient temperature changes, the driving ability of the autonomous mobile robot decreases, and its load-bearing capacity also changes, making the scheduling of transportation tasks more difficult. The use of conventional scheduling schemes may cause the robot to get stuck, move slowly, or cause damage to the robot. Summary of the invention

[0004] Based on the above problems, the present invention proposes an intelligent scheduling method and system for an autonomous mobile robot, which can ensure that the autonomous mobile robot can complete the transportation task stably and efficiently.

[0005] In view of this, a first aspect of the present invention proposes an intelligent scheduling method for an autonomous mobile robot, comprising: Constructing a dispatch queue of the autonomous mobile robot and a number of loading queues corresponding to the loading sites and a number of unloading queues corresponding to the unloading sites; When any autonomous mobile robot enters an idle state, recalculating the carrying capacity of the autonomous mobile robot; Adding an autonomous mobile robot in an idle state to the scheduling queue; Reading a list of items to be loaded corresponding to each loading station, wherein the list of items to be loaded includes volume information and weight information of each item to be loaded; matching the items to be loaded for the autonomous mobile robots in the dispatching queue in the list of items to be loaded according to the carrying capacity of each autonomous mobile robot in the dispatching queue; The autonomous mobile robot is moved from the dispatching queue to a loading queue corresponding to a loading station where the matched object to be loaded is located.

[0006] Furthermore, the step of recalculating the carrying capacity of the autonomous mobile robot specifically includes: Obtaining the open circuit voltage of the power battery of the autonomous mobile robot And remaining power ; Determine the remaining power of the power battery of the autonomous mobile robot Discharge limit voltage under ; According to the open circuit voltage and the discharge limit voltage Calculate the maximum discharge power of the power battery of the autonomous mobile robot ; According to the maximum discharge power of the power battery of the autonomous mobile robot Determine the maximum load of the autonomous mobile robot .

[0007] Further, according to the open circuit voltage and the discharge limit voltage Calculate the maximum discharge power of the power battery of the autonomous mobile robot The steps specifically include: Construct an output power constraint model based on the power battery of the autonomous mobile robot: , in is the discharge current of the power battery of the autonomous mobile robot, is the ohmic internal resistance of the power battery of the autonomous mobile robot, and is the characteristic constant of the power battery of the autonomous mobile robot; Determine the maximum discharge current of the power battery of the autonomous mobile robot using the output power constraint model ; Calculate the maximum discharge power of the power battery of the autonomous mobile robot: .

[0008] Furthermore, the output power constraint model is used to determine the maximum discharge current of the power battery of the autonomous mobile robot. The steps specifically include: Define the difference function: ; Constructed to calculate the maximum discharge current Iterative calculation model: , in is an iteration count variable greater than or equal to 0, and is an integer; Iteratively calculate the maximum discharge current based on the iterative calculation model .

[0009] Further, the maximum discharge current is iteratively calculated based on the iterative calculation model The steps specifically include: For the difference function Take the first-order derivative: ; Initialize the iteration count variable And the initial current ; Get the pre-configured iteration precision ; Take 1 as the iteration count variable The iteration step length is calculated by loop iteration: ; Determine whether this iteration satisfies: ; when When After adding 1, perform iterative calculation again; when When the maximum discharge current is assigned .

[0010] Furthermore, according to the maximum discharge power of the power battery of the autonomous mobile robot Determine the maximum load of the autonomous mobile robot The steps specifically include: Calculate the maximum mechanical power of the autonomous mobile robot: , in is the motor efficiency coefficient, is the transmission efficiency coefficient; Configure the target moving speed of the autonomous mobile robot ,in The maximum moving speed of the autonomous mobile robot; Calculate the target moving speed of the autonomous mobile robot Maximum load under .

[0011] Further, the target moving speed of the autonomous mobile robot is calculated. Maximum load under The steps specifically include: Calculate the target moving speed of the autonomous mobile robot The first mechanical power required to overcome the deadweight is: , in is the rolling friction coefficient of the driving wheels of the autonomous mobile robot on the ground in its workplace, is the acceleration due to gravity, is the body weight of the autonomous mobile robot; Calculate the target moving speed of the autonomous mobile robot The second mechanical power for load is: ; According to the second mechanical power Calculate the maximum load of the autonomous mobile robot: .

[0012] Furthermore, the step of matching the items to be loaded in the list of items to be loaded for the autonomous mobile robots in the dispatching queue according to the carrying capacity of each autonomous mobile robot in the dispatching queue specifically includes: Generate a carrying capacity sequence according to the carrying capacity of each autonomous mobile robot in the scheduling queue, wherein each element in the carrying capacity sequence is a key-value pair corresponding to each autonomous mobile robot in the scheduling queue. Determine an item combination for generating a transport task in the list of items to be loaded at each loading station, so that the sum of the volume and / or weight of the item combination matches an element in the transport capacity sequence; The autonomous mobile robot corresponding to the element in the carrying capacity sequence that matches the combination of items is determined as the target autonomous mobile robot.

[0013] Furthermore, the step of determining an item combination for generating a transport task in the list of items to be loaded at each loading station so that the sum of the volume and / or weight of the item combination matches an element in the transport capacity sequence specifically includes: Determine a temporary variable and initialize it as ; Determined in the said load list The items to be loaded constitute the first temporary item combination and The items to be loaded constitute a second temporary item combination; Calculate the sum of the carrying volume and the sum of the weight of the first temporary item combination: ,as well as The sum of the carrying volume and the sum of the weight of the second temporary item combination: , in 1 to A positive integer between The temporary item combination The carrying volume of items, The temporary item combination The weight of the item; Determine whether the first temporary item combination and the second temporary item combination satisfy: ,or , in 1 to A positive integer between is the number of key-value pairs in the carrying capacity sequence, is the first in the carrying capacity sequence The carrying capacity of key-value pairs, is the first in the carrying capacity sequence The amount of weight that can be carried by key-value pairs; When the first temporary item combination and the second temporary item combination do not meet any of the above conditions, the temporary variable After the loop is executed, the load list is determined The items to be loaded constitute the first temporary item combination and The items to be loaded constitute the second temporary item combination and its subsequent steps.

[0014] A second aspect of the present invention provides an intelligent scheduling system for an autonomous mobile robot, comprising: A queue construction module is used to construct a dispatch queue of the autonomous mobile robot and a plurality of loading queues corresponding to the loading sites and a plurality of unloading queues corresponding to the unloading sites; A carrying capacity calculation module, used for recalculating the carrying capacity of any autonomous mobile robot when the autonomous mobile robot enters an idle state; A dispatch queue management module, used to add an autonomous mobile robot in an idle state to the dispatch queue; A module for reading the list of items to be loaded, used to read the list of items to be loaded corresponding to each loading station, wherein the list of items to be loaded includes the volume information and weight information of each item to be loaded; A to-be-loaded object matching module, configured to match the to-be-loaded objects in the to-be-loaded object list for the autonomous mobile robots in the scheduling queue according to the carrying capacity of each autonomous mobile robot in the scheduling queue; The loading queue management module is used to move the autonomous mobile robot from the dispatching queue to the loading queue corresponding to the loading site where the matched object to be loaded is located.

[0015] The present invention proposes an intelligent scheduling method and system for autonomous mobile robots. By constructing a scheduling queue of autonomous mobile robots and a plurality of loading queues corresponding to loading sites and a plurality of unloading queues corresponding to unloading sites, when any autonomous mobile robot enters an idle state, the carrying capacity of the autonomous mobile robot is recalculated, the autonomous mobile robot in the idle state is added to the scheduling queue, the list of items to be loaded corresponding to each loading site is read, and the items to be loaded are matched for the autonomous mobile robots in the scheduling queue in the list of items to be loaded according to the carrying capacity of each autonomous mobile robot in the scheduling queue, and the autonomous mobile robot is moved from the scheduling queue to the loading queue corresponding to the loading site where the matched items to be loaded are located, so as to ensure that the autonomous mobile robot can complete the transportation task stably and efficiently. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of an intelligent scheduling method for an autonomous mobile robot provided by an embodiment of the present invention; Figure 2 It is a schematic block diagram of an intelligent scheduling system for an autonomous mobile robot provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0019] In the description of the present invention, the term "multiple" refers to two or more. Unless otherwise clearly defined, the orientation or positional relationship indicated by the terms "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation of the present invention. The terms "connection", "installation", "fixation", etc. should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. In addition, the terms "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first", "second", etc. can explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, the meaning of "multiple" is two or more.

[0020] In the description of this specification, the description of the terms "one embodiment", "some implementations", "specific embodiments", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0021] An intelligent scheduling method and system for an autonomous mobile robot provided according to some embodiments of the present invention will be described below with reference to the accompanying drawings.

[0022] like Figure 1 As shown, the first aspect of the present invention proposes an intelligent scheduling method for an autonomous mobile robot, comprising: Constructing a dispatch queue of the autonomous mobile robot and a number of loading queues corresponding to the loading sites and a number of unloading queues corresponding to the unloading sites; When any autonomous mobile robot enters an idle state, recalculating the carrying capacity of the autonomous mobile robot; Adding an autonomous mobile robot in an idle state to the scheduling queue; Reading a list of items to be loaded corresponding to each loading station, wherein the list of items to be loaded includes volume information and weight information of each item to be loaded; matching the items to be loaded for the autonomous mobile robots in the dispatching queue in the list of items to be loaded according to the carrying capacity of each autonomous mobile robot in the dispatching queue; The autonomous mobile robot is moved from the dispatching queue to a loading queue corresponding to a loading station where the matched object to be loaded is located.

[0023] Specifically, the dispatch queue is a device queue composed of autonomous mobile robots in an idle state, which may be autonomous mobile robots that enter the idle state after completing the last work task, or autonomous mobile robots that enter the idle state after completing charging. In the technical solution of the present invention, the idle state means that the autonomous mobile robot can accept new transportation tasks at any time. When an autonomous mobile robot is in a moving state or a charging state, it is considered to be in a non-idle state.

[0024] The loading site is a specific location where goods or workpieces are loaded onto the autonomous mobile robot, which may be one or more pre-specified locations. The loading queue is a device queue composed of autonomous mobile robots waiting to be loaded at the loading site, so the loading queue has a one-to-one correspondence with the loading site. Similarly, the unloading site is a specific location where goods or workpieces are unloaded from the autonomous mobile robot, which is usually one or more target locations corresponding to the transportation task. The unloading queue is a device queue composed of autonomous mobile robots waiting to be unloaded at the unloading site, so the unloading queue has a one-to-one correspondence with the unloading site.

[0025] The carrying capacity of the autonomous mobile robot is represented by the maximum carrying volume and the maximum carrying weight of the autonomous mobile robot.

[0026] In the list of items to be loaded, each item to be loaded is the smallest unit that can be transported independently. Each item to be loaded has a unique number as its unique identity, and the list of items to be loaded is composed of the numbers of all items to be loaded in the corresponding loading station.

[0027] Furthermore, the step of moving the autonomous mobile robot from the dispatching queue to a loading queue corresponding to a loading station where the matched object to be loaded is located specifically includes: Determine the objects to be loaded matched by the autonomous mobile robot. When there are multiple objects to be loaded matched by the same autonomous mobile robot, they should belong to the objects in the same loading station; Determine the site number of the loading site where the object to be loaded matched by the autonomous mobile robot is located; Determine the loading queue number corresponding to the site number according to the site number; Adding the autonomous mobile robot to a loading queue corresponding to the loading site number; The autonomous mobile robot is deleted from the scheduling queue.

[0028] Furthermore, the step of recalculating the carrying capacity of the autonomous mobile robot specifically includes: Obtaining the open circuit voltage of the power battery of the autonomous mobile robot And remaining power ; Determine the remaining power of the power battery of the autonomous mobile robot Discharge limit voltage under ; According to the open circuit voltage and the discharge limit voltage Calculate the maximum discharge power of the power battery of the autonomous mobile robot ; According to the maximum discharge power of the power battery of the autonomous mobile robot Determine the maximum load of the autonomous mobile robot .

[0029] Specifically, the open circuit voltage of the power battery of the autonomous mobile robot is The remaining power of the power battery of the autonomous mobile robot can be measured by its internal circuit monitoring circuit. Usually presented as a percentage, the open circuit voltage of the power battery of the autonomous mobile robot With remaining power The remaining power of the power battery of the autonomous mobile robot can be obtained by the characteristic curve between .

[0030] The discharge limit voltage refers to the critical voltage at which continued discharge of the power battery of the autonomous mobile robot may cause irreversible damage to the battery corresponding to different remaining power states. The irreversible damage mentioned here includes performance degradation and shortened life of the power battery of the autonomous mobile robot due to excessive discharge.

[0031] Discharge limit voltage of the power battery of the autonomous mobile robot Different values ​​are shown in different residual power states, and different types of power batteries have different discharge limit voltages in different residual power states. Discharge limit voltage under The remaining power for each percentage value is obtained through a large number of experimental tests on the same type of batteries in a laboratory environment. , which will have a pre-measured and configured discharge limit voltage .

[0032] Further, according to the open circuit voltage and the discharge limit voltage Calculate the maximum discharge power of the power battery of the autonomous mobile robot The steps specifically include: Construct an output power constraint model based on the power battery of the autonomous mobile robot: , in is the discharge current of the power battery of the autonomous mobile robot, is the ohmic internal resistance of the power battery of the autonomous mobile robot, and is the characteristic constant of the power battery of the autonomous mobile robot; Determine the maximum discharge current of the power battery of the autonomous mobile robot using the output power constraint model ; Calculate the maximum discharge power of the power battery of the autonomous mobile robot: .

[0033] Specifically, the ohmic internal resistance of the power battery of the autonomous mobile robot is It is a part of the internal resistance of the power battery. Its resistance value is relatively fixed and has nothing to do with the discharge current of the power battery.

[0034] In the technical solution of the above embodiment, the output power constraint model is a model for characterizing the open circuit voltage of the power battery of the autonomous mobile robot. A simplified model of the functional relationship between and its discharge current.

[0035] The characteristic constants in the output power constraint model and It is a characteristic constant of the functional relationship between the discharge current and polarization internal resistance of the power battery used to constitute the autonomous mobile robot, measured in a laboratory environment. The maximum discharge power of the power battery of the autonomous mobile robot can be analyzed through the output power constraint model. .

[0036] Furthermore, the output power constraint model is used to determine the maximum discharge current of the power battery of the autonomous mobile robot. The steps specifically include: Define the difference function: ; Constructed to calculate the maximum discharge current Iterative calculation model: , in is an iteration count variable greater than or equal to 0, and is an integer; Iteratively calculate the maximum discharge current based on the iterative calculation model .

[0037] Further, the maximum discharge current is iteratively calculated based on the iterative calculation model The steps specifically include: For the difference function Take the first-order derivative: ; Initialize the iteration count variable And the initial current ; Get the pre-configured iteration precision ; Take 1 as the iteration count variable The iteration step length is calculated by loop iteration: ; Determine whether this iteration satisfies: ; when When After adding 1, perform iterative calculation again; when When the maximum discharge current is assigned .

[0038] Specifically, the iteration accuracy is a pre-configured smaller value, which is used as the threshold of the difference between the discharge currents of two iterations and as the stop condition of the iteration process. is less than the maximum discharge current The discharge current can be obtained by measuring the discharge current of the power battery of the autonomous mobile robot and randomly sampling. Preferably, the initial current is the maximum value among several measured values ​​of the discharge current of the power battery of the autonomous mobile robot. The larger the maximum discharge current The smaller the difference, the shorter the iteration time.

[0039] Furthermore, according to the maximum discharge power of the power battery of the autonomous mobile robot Determine the maximum load of the autonomous mobile robot The steps specifically include: Calculate the maximum mechanical power of the autonomous mobile robot: , in is the motor efficiency coefficient, is the transmission efficiency coefficient; Configure the target moving speed of the autonomous mobile robot ,in The maximum moving speed of the autonomous mobile robot; Calculate the target moving speed of the autonomous mobile robot Maximum load under .

[0040] The motor efficiency coefficient Indicates the efficiency of the motor in converting electrical energy into mechanical energy, and the transmission efficiency coefficient It indicates the energy transfer efficiency during the transmission process from the motor to the drive wheel. and the transmission efficiency coefficient The target moving speed of the autonomous mobile robot is measured in a laboratory environment. A pre-configured maximum moving speed smaller than the maximum moving speed of the autonomous mobile robot The numerical value of .

[0041] Further, the target moving speed of the autonomous mobile robot is calculated. Maximum load under The steps specifically include: Calculate the target moving speed of the autonomous mobile robot The first mechanical power required to overcome the deadweight is: , in is the rolling friction coefficient of the driving wheels of the autonomous mobile robot on the ground in its workplace, is the acceleration due to gravity, is the body weight of the autonomous mobile robot; Calculate the target moving speed of the autonomous mobile robot The second mechanical power for load is: ; According to the second mechanical power Calculate the maximum load of the autonomous mobile robot: .

[0042] The rolling friction coefficient It is related to the material of the driving wheel of the autonomous mobile robot and the ground material of its workplace. When there are multiple different ground materials in the workplace of the autonomous mobile robot, the rolling friction coefficient between the ground material in the workplace with the largest friction with the driving wheel material of the autonomous mobile robot is taken as the rolling friction coefficient. Usually the value is . Describe the maximum moving speed of the autonomous mobile robot The maximum mechanical power of the autonomous mobile robot The maximum moving speed when all the friction generated by the weight is used to overcome it satisfies: .

[0043] Furthermore, the step of matching the items to be loaded in the list of items to be loaded for the autonomous mobile robots in the dispatching queue according to the carrying capacity of each autonomous mobile robot in the dispatching queue specifically includes: Generate a carrying capacity sequence according to the carrying capacity of each autonomous mobile robot in the scheduling queue, wherein each element in the carrying capacity sequence is a key-value pair corresponding to each autonomous mobile robot in the scheduling queue. Determine an item combination for generating a transport task in the list of items to be loaded at each loading station, so that the sum of the volume and / or weight of the item combination matches an element in the transport capacity sequence; The autonomous mobile robot corresponding to the element in the carrying capacity sequence that matches the combination of items is determined as the target autonomous mobile robot.

[0044] Specifically, the carrying capacity sequence is the same length as the scheduling queue, that is, the number of key-value pairs in the carrying capacity sequence is the same as the number of autonomous mobile robots in the scheduling queue, and the two have a one-to-one correspondence. The carrying volume value in each "carryable volume, carryable weight" key-value pair in the carrying volume sequence corresponds to the maximum carryable volume of each autonomous mobile robot in the scheduling queue. Similarly, the carrying weight value in each "carryable volume, carryable weight" key-value pair in the carrying weight sequence corresponds to the maximum carryable weight of each autonomous mobile robot in the scheduling queue.

[0045] Furthermore, in the step of determining an item combination for generating a transport task in the list of items to be loaded at each loading station, the item combination is a subset of the list of items to be loaded, which is composed of the numbers of the items required to be transported for the corresponding transport task.

[0046] Furthermore, after the step of determining the autonomous mobile robot corresponding to the element in the carrying capacity sequence that matches the item combination as the target autonomous mobile robot, it also includes determining the items to be loaded in the item combination as the items to be loaded that match the autonomous mobile robot.

[0047] Furthermore, the step of determining an item combination for generating a transport task in the list of items to be loaded at each loading station so that the sum of the volume and / or weight of the item combination matches an element in the transport capacity sequence specifically includes: Determine a temporary variable and initialize it as ; Determined in the said load list The items to be loaded constitute the first temporary item combination and The items to be loaded constitute a second temporary item combination; Calculate the sum of the carrying volume and the sum of the weight of the first temporary item combination: ,as well as The sum of the carrying volume and the sum of the weight of the second temporary item combination: , in 1 to A positive integer between The temporary item combination The carrying volume of items, The temporary item combination The weight of the item; Determine whether the first temporary item combination and the second temporary item combination satisfy: ,or , in 1 to A positive integer between is the number of key-value pairs in the carrying capacity sequence, is the first in the carrying capacity sequence The carrying capacity of key-value pairs, is the first in the carrying capacity sequence The amount of weight that can be carried by key-value pairs; When the first temporary item combination and the second temporary item combination do not meet any of the above conditions, the temporary variable After the loop is executed, the load list is determined The items to be loaded constitute the first temporary item combination and The items to be loaded constitute the second temporary item combination and its subsequent steps.

[0048] It should be noted that the carrying volume is not the actual volume of the items to be loaded, but the sum of the actual volume of the items to be loaded and a pre-configured redundancy value, so as to include the volume occupied by the gaps between multiple items to be loaded when they are placed in the loading tray of the autonomous mobile robot into the calculation. For items to be loaded of different shapes and materials, their redundancy values ​​are configured to different values.

[0049] The first temporary item combination and the second temporary item combination do not satisfy any of the above conditions, which means that the first temporary item combination and the second temporary item combination do not satisfy: , and does not satisfy: .

[0050] Further, when determining whether the first temporary item combination and the second temporary item combination satisfy: ,or After the steps, it also includes: When the first temporary item combination and the second temporary item combination satisfy one of the above conditions, or both of them, the first item combination is determined as the item combination.

[0051] Furthermore, when the first temporary item combination and the second temporary item combination satisfy When the scheduling queue determines that autonomous mobile robots to form a first autonomous mobile robot list; Calculate the difference between the transportable volume of each autonomous mobile robot in the first autonomous mobile robot list and the sum of the transportable volumes of the first temporary item combination: , in 1 to A positive integer between the number of autonomous mobile robots in the first autonomous mobile robot list, is the carrying volume of the th autonomous mobile robot in the first autonomous mobile robot list; A target autonomous mobile robot is determined in the first autonomous mobile robot list, so that the target autonomous mobile robot satisfies: , in is the transportable volume of the target autonomous mobile robot.

[0052] Furthermore, when the first temporary item combination and the second temporary item combination satisfy When the scheduling queue determines that autonomous mobile robots to form a second autonomous mobile robot list; Calculate the difference between the carryable weight of each autonomous mobile robot in the second autonomous mobile robot list and the sum of the carryable weights of the first temporary object combination: , in 1 to A positive integer between is the number of autonomous mobile robots in the second autonomous mobile robot list, The first autonomous mobile robot in the list The load capacity of an autonomous mobile robot; A target autonomous mobile robot is determined in the second autonomous mobile robot list, so that the target autonomous mobile robot satisfies: , in The loadable weight of the target autonomous mobile robot.

[0053] like Figure 2 As shown, the second aspect of the present invention proposes an intelligent scheduling system for an autonomous mobile robot, comprising: A queue construction module is used to construct a dispatch queue of the autonomous mobile robot and a plurality of loading queues corresponding to the loading sites and a plurality of unloading queues corresponding to the unloading sites; A carrying capacity calculation module, used for recalculating the carrying capacity of any autonomous mobile robot when the autonomous mobile robot enters an idle state; A dispatch queue management module, used to add an autonomous mobile robot in an idle state to the dispatch queue; A module for reading the list of items to be loaded, used to read the list of items to be loaded corresponding to each loading station, wherein the list of items to be loaded includes the volume information and weight information of each item to be loaded; A to-be-loaded object matching module, configured to match the to-be-loaded objects in the to-be-loaded object list for the autonomous mobile robots in the scheduling queue according to the carrying capacity of each autonomous mobile robot in the scheduling queue; The loading queue management module is used to move the autonomous mobile robot from the dispatching queue to the loading queue corresponding to the loading site where the matched object to be loaded is located.

[0054] Specifically, the dispatch queue is a device queue composed of autonomous mobile robots in an idle state, which may be autonomous mobile robots that enter the idle state after completing the last work task, or autonomous mobile robots that enter the idle state after completing charging. In the technical solution of the present invention, the idle state means that the autonomous mobile robot can accept new transportation tasks at any time. When an autonomous mobile robot is in a moving state or a charging state, it is considered to be in a non-idle state.

[0055] The loading site is a specific location where goods or workpieces are loaded onto the autonomous mobile robot, which may be one or more pre-specified locations. The loading queue is a device queue composed of autonomous mobile robots waiting to be loaded at the loading site, so the loading queue has a one-to-one correspondence with the loading site. Similarly, the unloading site is a specific location where goods or workpieces are unloaded from the autonomous mobile robot, which is usually one or more target locations corresponding to the transportation task. The unloading queue is a device queue composed of autonomous mobile robots waiting to be unloaded at the unloading site, so the unloading queue has a one-to-one correspondence with the unloading site.

[0056] The carrying capacity of the autonomous mobile robot is represented by the maximum carrying volume and the maximum carrying weight of the autonomous mobile robot.

[0057] In the list of items to be loaded, each item to be loaded is the smallest unit that can be transported independently. Each item to be loaded has a unique number as its unique identity, and the list of items to be loaded is composed of the numbers of all items to be loaded in the corresponding loading station.

[0058] Furthermore, the loading queue management module specifically includes: A module for determining objects to be loaded, used to determine the objects to be loaded matched by the autonomous mobile robot. When there are multiple objects to be loaded matched by the same autonomous mobile robot, they should belong to the objects in the same loading station; A site number determination module, used to determine the site number of the loading site where the object to be loaded matched by the autonomous mobile robot is located; A loading queue number determination module, used to determine the loading queue number corresponding to the site number according to the site number; An autonomous mobile robot adding module, used to add the autonomous mobile robot to the loading queue corresponding to the loading site number; The autonomous mobile robot deletion module is used to delete the autonomous mobile robot from the scheduling queue.

[0059] Furthermore, the carrying capacity calculation module specifically includes: A battery parameter acquisition module is used to obtain the open circuit voltage of the power battery of the autonomous mobile robot. And remaining power ; The discharge limit voltage determination module is used to determine the remaining power of the power battery of the autonomous mobile robot. Discharge limit voltage under ; The maximum discharge power calculation module is used to calculate the maximum discharge power according to the open circuit voltage and the discharge limit voltage Calculate the maximum discharge power of the power battery of the autonomous mobile robot ; The maximum load determination module is used to determine the maximum discharge power of the power battery of the autonomous mobile robot. Determine the maximum load of the autonomous mobile robot .

[0060] Specifically, the open circuit voltage of the power battery of the autonomous mobile robot is The remaining power of the power battery of the autonomous mobile robot can be measured by its internal circuit monitoring circuit. Usually presented as a percentage, the open circuit voltage of the power battery of the autonomous mobile robot Remaining power The remaining power of the power battery of the autonomous mobile robot can be obtained by the characteristic curve between .

[0061] The discharge limit voltage refers to the critical voltage at which continued discharge of the power battery of the autonomous mobile robot may cause irreversible damage to the battery corresponding to different remaining power states. The irreversible damage mentioned here includes performance degradation and shortened life of the power battery of the autonomous mobile robot due to excessive discharge.

[0062] Discharge limit voltage of the power battery of the autonomous mobile robot Different values ​​are shown in different residual power states, and different types of power batteries have different discharge limit voltages in different residual power states. Discharge limit voltage under The remaining power for each percentage value is obtained through a large number of experimental tests on the same type of batteries in a laboratory environment. , which will have a pre-measured and configured discharge limit voltage .

[0063] Furthermore, the maximum discharge power calculation module specifically includes: An output power constraint model building module is used to build an output power constraint model based on the power battery of the autonomous mobile robot: , in is the discharge current of the power battery of the autonomous mobile robot, is the ohmic internal resistance of the power battery of the autonomous mobile robot, and is the characteristic constant of the power battery of the autonomous mobile robot; A maximum discharge current determination module is used to determine the maximum discharge current of the power battery of the autonomous mobile robot using the output power constraint model ; The maximum discharge power calculation module is specifically used to calculate the maximum discharge power of the power battery of the autonomous mobile robot using the following formula: .

[0064] Specifically, the ohmic internal resistance of the power battery of the autonomous mobile robot is It is a part of the internal resistance of the power battery. Its resistance value is relatively fixed and has nothing to do with the discharge current of the power battery.

[0065] In the technical solution of the above embodiment, the output power constraint model is a model for characterizing the open circuit voltage of the power battery of the autonomous mobile robot. A simplified model of the functional relationship between and its discharge current.

[0066] The characteristic constants in the output power constraint model and It is a characteristic constant of the functional relationship between the discharge current and polarization internal resistance of the power battery used to constitute the autonomous mobile robot, measured in a laboratory environment. The maximum discharge power of the power battery of the autonomous mobile robot can be analyzed through the output power constraint model. .

[0067] Furthermore, the maximum discharge current determination module specifically includes: The difference function definition module is used to define the difference function: ; Iterative calculation model building module, used to build a model for calculating the maximum discharge current Iterative calculation model: , in is an iteration count variable greater than or equal to 0, and is an integer; The maximum discharge current determination module is specifically configured to iteratively calculate the maximum discharge current based on the iterative calculation model. .

[0068] Furthermore, the maximum discharge current determination module also includes: A first-order derivative calculation module is used to calculate the difference function Take the first-order derivative: ; Iteration parameter initialization module, used to initialize the iteration count variable And the initial current ; Iteration accuracy acquisition module, used to obtain pre-configured iteration accuracy ; A loop iteration calculation module is used to take 1 as the iteration count variable The iteration step length is calculated by loop iteration: ; Iteration condition judgment module, used to judge whether this iteration meets the following conditions: ; The loop iteration calculation module is specifically used to When After adding 1, perform iterative calculation again; The maximum discharge current assignment module is used to When the maximum discharge current is assigned .

[0069] Specifically, the iteration accuracy is a pre-configured smaller value, which is used as the threshold of the difference between the discharge currents of two iterations and as the stop condition of the iteration process. is less than the maximum discharge current The discharge current can be obtained by measuring the discharge current of the power battery of the autonomous mobile robot and randomly sampling. Preferably, the initial current is the maximum value among several measured values ​​of the discharge current of the power battery of the autonomous mobile robot. The larger the maximum discharge current The smaller the difference, the shorter the iteration time.

[0070] Furthermore, the maximum load determination module specifically includes: The maximum mechanical power calculation module is used to calculate the maximum mechanical power of the autonomous mobile robot: , in is the motor efficiency coefficient, is the transmission efficiency coefficient; A target moving speed configuration module is used to configure the target moving speed of the autonomous mobile robot ,in The maximum moving speed of the autonomous mobile robot; The maximum load determination module is specifically used to calculate the target moving speed of the autonomous mobile robot. Maximum load under .

[0071] The motor efficiency coefficient Indicates the efficiency of the motor in converting electrical energy into mechanical energy, and the transmission efficiency coefficient It indicates the energy transfer efficiency during the transmission process from the motor to the drive wheel. and the transmission efficiency coefficient The target moving speed of the autonomous mobile robot is measured in a laboratory environment. A pre-configured maximum moving speed smaller than the maximum moving speed of the autonomous mobile robot The numerical value of .

[0072] Furthermore, the maximum load determination module further includes: The first mechanical power calculation module is used to calculate the target moving speed of the autonomous mobile robot. The first mechanical power required to overcome the deadweight is: , in is the rolling friction coefficient of the driving wheels of the autonomous mobile robot on the ground in its workplace, is the acceleration due to gravity, is the body weight of the autonomous mobile robot; The second mechanical power calculation module is used to calculate the target moving speed of the autonomous mobile robot. The second mechanical power for load is: ; The maximum load determination module is specifically configured to determine the maximum load according to the second mechanical power Calculate the maximum load of the autonomous mobile robot: .

[0073] The rolling friction coefficient It is related to the material of the driving wheel of the autonomous mobile robot and the ground material of its workplace. When there are multiple different ground materials in the workplace of the autonomous mobile robot, the rolling friction coefficient between the ground material with the largest friction between the driving wheel material of the autonomous mobile robot in the workplace is taken as the rolling friction coefficient. The gravitational acceleration Usually the value is The maximum moving speed of the autonomous mobile robot The maximum mechanical power of the autonomous mobile robot The maximum moving speed when all the friction generated by the weight is used to overcome it satisfies: .

[0074] Furthermore, the module for matching items to be loaded specifically includes: A carrying capacity sequence generation module, used to generate a carrying capacity sequence according to the carrying capacity of each autonomous mobile robot in the scheduling queue, wherein each element in the carrying capacity sequence is a key-value pair of "carryable volume, carryable weight" corresponding to each autonomous mobile robot in the scheduling queue; An article combination determination module, used to determine an article combination for generating a transport task in the list of articles to be loaded at each loading station, so that the sum of the volume and / or weight of the article combination matches an element in the transport capacity sequence; The target autonomous mobile robot determination module is used to determine the autonomous mobile robot corresponding to the element in the carrying capacity sequence that matches the combination of items as the target autonomous mobile robot.

[0075] Specifically, the carrying capacity sequence is the same length as the scheduling queue, that is, the number of key-value pairs in the carrying capacity sequence is the same as the number of autonomous mobile robots in the scheduling queue, and the two have a one-to-one correspondence. The carrying volume value in each "carryable volume, carryable weight" key-value pair in the carrying volume sequence corresponds to the maximum carryable volume of each autonomous mobile robot in the scheduling queue. Similarly, the carrying weight value in each "carryable volume, carryable weight" key-value pair in the carrying weight sequence corresponds to the maximum carryable weight of each autonomous mobile robot in the scheduling queue.

[0076] Furthermore, in the article combination determination module, the article combination is a subset of the list of articles to be loaded, which is composed of the numbers of the articles required to be transported by the corresponding transportation task.

[0077] Furthermore, the to-be-loaded object matching module is further used to determine the to-be-loaded objects matched by the autonomous mobile robot from the to-be-loaded objects in the object combination.

[0078] Furthermore, the item combination determination module specifically includes: Temporary variable initialization module, used to determine a temporary variable and initialize it as ; A temporary item combination generation module is used to determine in the loading item list The items to be loaded constitute the first temporary item combination and The items to be loaded constitute a second temporary item combination; The volume and weight accumulation module is used to calculate the sum of the carrying volume and the sum of the weight of the first temporary item combination: ,as well as The sum of the carrying volume and the sum of the weight of the second temporary item combination: , in 1 to A positive integer between The temporary item combination The carrying volume of items, The temporary item combination The weight of the item; A boundary judgment module is used to judge whether the first temporary item combination and the second temporary item combination meet the following requirements: ,or , in 1 to A positive integer between is the number of key-value pairs in the carrying capacity sequence, is the first in the carrying capacity sequence The carrying capacity of key-value pairs, is the first in the carrying capacity sequence The amount of weight that can be carried by key-value pairs; A loop execution module is used to set the temporary variable After the loop is executed, the load list is determined The items to be loaded constitute the first temporary item combination and The items to be loaded constitute the second temporary item combination and its subsequent steps.

[0079] It should be noted that the carrying volume is not the actual volume of the items to be loaded, but the sum of the actual volume of the items to be loaded and a pre-configured redundancy value, so as to include the volume occupied by the gaps between multiple items to be loaded when they are placed in the loading tray of the autonomous mobile robot into the calculation. For items to be loaded of different shapes and materials, their redundancy values ​​are configured to different values.

[0080] The first temporary item combination and the second temporary item combination do not satisfy any of the above conditions, which means that the first temporary item combination and the second temporary item combination do not satisfy: , and does not satisfy: Furthermore, the item combination determining module is further configured to determine the first item combination as the item combination when the first temporary item combination and the second temporary item combination satisfy one of the above conditions, or both of them.

[0081] Furthermore, the item combination determination module further includes: The first autonomous mobile robot list generation module is used to generate a list of items when the first temporary item combination and the second temporary item combination meet the requirements. When the scheduling queue determines that autonomous mobile robots to form a first autonomous mobile robot list; A first difference calculation module is used to calculate the difference between the carrying volume of each autonomous mobile robot in the first autonomous mobile robot list and the sum of the carrying volumes of the first temporary item combination: , in 1 to A positive integer between the number of autonomous mobile robots in the first autonomous mobile robot list, is the carrying volume of the th autonomous mobile robot in the first autonomous mobile robot list; The target autonomous mobile robot determination module is specifically configured to determine a target autonomous mobile robot in the first autonomous mobile robot list, such that the target autonomous mobile robot satisfies: , in is the transportable volume of the target autonomous mobile robot.

[0082] Furthermore, the item combination determination module further includes: The second autonomous mobile robot list generating module is used to generate a list of items when the first temporary item combination and the second temporary item combination meet the requirements. When the scheduling queue determines that autonomous mobile robots to form a second autonomous mobile robot list; The second difference calculation module is used to calculate the difference between the carryable weight of each autonomous mobile robot in the second autonomous mobile robot list and the sum of the carryable weights of the first temporary item combination: , in 1 to A positive integer between is the number of autonomous mobile robots in the second autonomous mobile robot list, The first autonomous mobile robot in the list The load capacity of an autonomous mobile robot; The target autonomous mobile robot determination module is specifically configured to determine a target autonomous mobile robot in the second autonomous mobile robot list, such that the target autonomous mobile robot satisfies: , in The loadable weight of the target autonomous mobile robot.

[0083] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0084] According to the embodiments of the present invention as described above, these embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and changes can be made based on the above description. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can make good use of the present invention and the modified use based on the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent scheduling method for an autonomous mobile robot, characterized in that: include: Constructing a dispatch queue of the autonomous mobile robot and a number of loading queues corresponding to the loading sites and a number of unloading queues corresponding to the unloading sites; When any autonomous mobile robot enters an idle state, recalculating the carrying capacity of the autonomous mobile robot; Adding an autonomous mobile robot in an idle state to the scheduling queue; Reading a list of items to be loaded corresponding to each loading station, wherein the list of items to be loaded includes volume information and weight information of each item to be loaded; matching the items to be loaded for the autonomous mobile robots in the dispatching queue in the list of items to be loaded according to the carrying capacity of each autonomous mobile robot in the dispatching queue; The autonomous mobile robot is moved from the dispatching queue to a loading queue corresponding to a loading station where the matched object to be loaded is located.

2. The intelligent scheduling method for an autonomous mobile robot according to claim 1, characterized in that: The step of recalculating the carrying capacity of the autonomous mobile robot specifically includes: Obtaining the open circuit voltage of the power battery of the autonomous mobile robot And remaining power ; Determine the remaining power of the power battery of the autonomous mobile robot Discharge limit voltage under ; According to the open circuit voltage and the discharge limit voltage Calculate the maximum discharge power of the power battery of the autonomous mobile robot ; According to the maximum discharge power of the power battery of the autonomous mobile robot Determine the maximum load of the autonomous mobile robot .

3. The intelligent scheduling method for an autonomous mobile robot according to claim 2, characterized in that: According to the open circuit voltage and the discharge limit voltage Calculate the maximum discharge power of the power battery of the autonomous mobile robot The steps specifically include: Construct an output power constraint model based on the power battery of the autonomous mobile robot: ， in is the discharge current of the power battery of the autonomous mobile robot, is the ohmic internal resistance of the power battery of the autonomous mobile robot, and is the characteristic constant of the power battery of the autonomous mobile robot; Determine the maximum discharge current of the power battery of the autonomous mobile robot using the output power constraint model ; Calculate the maximum discharge power of the power battery of the autonomous mobile robot: 。 4. The intelligent scheduling method for an autonomous mobile robot according to claim 3, characterized in that: Determine the maximum discharge current of the power battery of the autonomous mobile robot using the output power constraint model The steps specifically include: Define the difference function: ； Constructed to calculate the maximum discharge current Iterative calculation model: ， in is an iteration count variable greater than or equal to 0, and is an integer; Iteratively calculate the maximum discharge current based on the iterative calculation model .

5. The intelligent scheduling method for an autonomous mobile robot according to claim 4, characterized in that: Iteratively calculate the maximum discharge current based on the iterative calculation model The steps specifically include: For the difference function Take the first-order derivative: ； Initialize the iteration count variable And the initial current ; Get the pre-configured iteration precision ; Take 1 as the iteration count variable The iteration step length is calculated by loop iteration: ； Determine whether this iteration satisfies: ； when When After adding 1, perform iterative calculation again; when When the maximum discharge current is assigned .

6. The intelligent scheduling method for an autonomous mobile robot according to claim 3, characterized in that: According to the maximum discharge power of the power battery of the autonomous mobile robot Determine the maximum load of the autonomous mobile robot The steps specifically include: Calculate the maximum mechanical power of the autonomous mobile robot: ， in is the motor efficiency coefficient, is the transmission efficiency coefficient; Configure the target moving speed of the autonomous mobile robot ,in The maximum moving speed of the autonomous mobile robot; Calculate the target moving speed of the autonomous mobile robot Maximum load under .

7. The intelligent scheduling method for an autonomous mobile robot according to claim 6, characterized in that: Calculate the target moving speed of the autonomous mobile robot Maximum load under The steps specifically include: Calculate the target moving speed of the autonomous mobile robot The first mechanical power required to overcome the deadweight is: ， in is the rolling friction coefficient of the driving wheels of the autonomous mobile robot on the ground in its workplace, is the acceleration due to gravity, is the body weight of the autonomous mobile robot; Calculate the target moving speed of the autonomous mobile robot The second mechanical power for load is: ； According to the second mechanical power Calculate the maximum load of the autonomous mobile robot: 。 8. The intelligent scheduling method for an autonomous mobile robot according to claim 2, characterized in that: The step of matching the items to be loaded in the list of items to be loaded for the autonomous mobile robots in the dispatching queue according to the carrying capacity of each autonomous mobile robot in the dispatching queue specifically includes: Generate a carrying capacity sequence according to the carrying capacity of each autonomous mobile robot in the scheduling queue, wherein each element in the carrying capacity sequence is a key-value pair corresponding to each autonomous mobile robot in the scheduling queue; Determine an item combination for generating a transport task in the list of items to be loaded at each loading station, so that the sum of the volume and / or weight of the item combination matches an element in the transport capacity sequence; The autonomous mobile robot corresponding to the element in the carrying capacity sequence that matches the combination of items is determined as the target autonomous mobile robot.

9. The intelligent scheduling method for an autonomous mobile robot according to claim 8, characterized in that: The step of determining an item combination for generating a transport task in the list of items to be loaded at each loading station so that the sum of the volume and / or weight of the item combination matches an element in the transport capacity sequence specifically includes: Determine a temporary variable and initialize it as ; Determined in the said load list The items to be loaded constitute the first temporary item combination and The items to be loaded constitute a second temporary item combination; Calculate the sum of the carrying volume and the sum of the weight of the first temporary item combination: ,as well as The sum of the carrying volume and the sum of the weight of the second temporary item combination: ， in 1 to A positive integer between The temporary item combination The carrying volume of items, The temporary item combination The weight of the item; Determine whether the first temporary item combination and the second temporary item combination satisfy: ,or ， in 1 to A positive integer between is the number of key-value pairs in the carrying capacity sequence, is the first in the carrying capacity sequence The carrying capacity of key-value pairs, is the first in the carrying capacity sequence The amount of weight that can be carried by key-value pairs; When the first temporary item combination and the second temporary item combination do not meet any of the above conditions, the temporary variable After the loop is executed, the load list is determined in The items to be loaded constitute the first temporary item combination and The items to be loaded constitute the second temporary item combination and its subsequent steps.

10. An intelligent scheduling system for an autonomous mobile robot, characterized in that: include: A queue construction module is used to construct a dispatch queue of the autonomous mobile robot and a plurality of loading queues corresponding to the loading sites and a plurality of unloading queues corresponding to the unloading sites; A carrying capacity calculation module, used for recalculating the carrying capacity of any autonomous mobile robot when the autonomous mobile robot enters an idle state; A dispatch queue management module, used to add an autonomous mobile robot in an idle state to the dispatch queue; An item list reading module is used to read the item list to be loaded corresponding to each loading station, wherein the item list to be loaded includes the volume information and weight information of each item to be loaded; A to-be-loaded object matching module, configured to match the to-be-loaded objects in the to-be-loaded object list for the autonomous mobile robots in the scheduling queue according to the carrying capacity of each autonomous mobile robot in the scheduling queue; The loading queue management module is used to move the autonomous mobile robot from the dispatching queue to the loading queue corresponding to the loading site where the matched object to be loaded is located.

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