An intelligent scheduling method and system for an autonomous mobile robot

Abstract

The present invention provides an intelligent scheduling method and system for an autonomous mobile robot. By constructing a scheduling queue for the autonomous mobile robot, a plurality of loading queues corresponding to loading stations, and a plurality of unloading queues corresponding to unloading stations, 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 station is read, and according to the carrying capacity of each autonomous mobile robot in the scheduling queue, items to be loaded are matched for the autonomous mobile robots in the scheduling queue in the list of items to be loaded. Then, the autonomous mobile robot is moved from the scheduling queue to the loading queue corresponding to the loading station where the matched item to be loaded is located, which can ensure that the autonomous mobile robot can complete the transportation task stably and efficiently.

Description

Technical Field

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

[0002] An AMR (Autonomous Mobile Robot) is a robot with autonomous movement ability and certain autonomous decision-making ability. It can autonomously navigate, plan paths, and execute specific work tasks in a specified environment without human intervention. These characteristics of AMR make it widely used in fields such as industrial manufacturing, logistics warehousing, agricultural production, and medical and health care. Especially in the short-distance load transportation of a large number of items, it greatly reduces the dependence on human labor in the transportation link and significantly improves the transportation efficiency.

[0003] In order to enable an autonomous mobile robot to have flexible autonomous movement ability, it usually uses a built-in power battery to provide power for autonomous movement. When the power of the power battery is sufficient, it can usually provide very strong driving ability. However, affected by factors such as battery loss and environmental temperature changes, the driving ability it can provide also decreases accordingly. This situation is more obvious when the autonomous mobile robot is carrying a load. For example, in the field of industrial manufacturing, the workpieces or auxiliary equipment to be transported are often heavy items. In a production workshop or a warehousing environment, when there are a large number of heavy objects to be transported, it is relatively common to use multiple autonomous mobile robots for cluster transportation. Affected by factors such as battery loss and environmental temperature changes, the driving ability of the autonomous mobile robot decreases, and its load-bearing capacity also changes accordingly, making the scheduling of transportation tasks more difficult. Using a conventional scheduling scheme may cause situations such as the robot getting stuck, moving slowly, or the robot being damaged. Summary of the Invention

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

[0005] In view of this, the first aspect of the present invention proposes an intelligent scheduling method for autonomous mobile robots, including:

[0006] Construct a scheduling queue for autonomous mobile robots, several loading queues corresponding to loading stations, and several unloading queues corresponding to unloading stations;

[0007] When any autonomous mobile robot enters the idle state, recalculate the carrying capacity of the autonomous mobile robot;

[0008] Add the autonomous mobile robot in the idle state to the scheduling queue;

[0009] Read the list of items to be loaded corresponding to each loading station, where the list of items to be loaded includes the volume information and weight information of each item to be loaded;

[0010] Match the items to be loaded 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;

[0011] Move the autonomous mobile robot from the scheduling queue to the loading queue corresponding to the loading station where the matched item to be loaded is located.

[0012] Further, the step of recalculating the carrying capacity of the autonomous mobile robot specifically includes:

[0013] Obtain the open-circuit voltage of the power battery of the autonomous mobile robot and the remaining battery level ;

[0014] Determine the discharge limit voltage of the power battery of the autonomous mobile robot at the remaining battery level ; ;

[0015] Calculate the maximum discharge power of the power battery of the autonomous mobile robot according to the open-circuit voltage and the discharge limit voltage ; ;

[0016] Determine the maximum load of the autonomous mobile robot according to the maximum discharge power of the power battery of the autonomous mobile robot ; .

[0017] Further, the step of calculating the maximum discharge power of the power battery of the autonomous mobile robot according to the open-circuit voltage and the discharge limit voltage specifically includes: Build an output power constraint model based on the power battery of the autonomous mobile robot:

[0018] ,

[0019] ,

[0020] where 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;

[0021] Use the output power constraint model to determine the maximum discharge current of the power battery of the autonomous mobile robot ;

[0022] Calculate the maximum discharge power of the power battery of the autonomous mobile robot:

[0023] .

[0024] Furthermore, the step of using the output power constraint model to determine the maximum discharge current of the power battery of the autonomous mobile robot specifically includes:

[0025] Define the difference function:

[0026] ;

[0027] Construct an iterative calculation model for calculating the maximum discharge current :

[0028] ,

[0029] where is an iterative count variable greater than or equal to 0, and is an integer;

[0030] Iteratively calculate the maximum discharge current based on the iterative calculation model .

[0031] Furthermore, the step of iteratively calculating the maximum discharge current based on the iterative calculation model specifically includes:

[0032] Take the first derivative of the difference function :

[0033] ;

[0034] Initialize the iterative count variable and the initial current ;

[0035] Obtain the pre-configured iteration accuracy ;

[0036] Use 1 as the iteration step of the iterative count variable to perform loop iterative calculation:

[0037] ;

[0038] Determine whether the current iteration meets the following conditions:

[0039] ;

[0040] When the iteration count variable is incremented by 1 and then the iterative calculation is performed again;

[0041] When the maximum discharge current .

[0042] Furthermore, the steps for determining the maximum load of the autonomous mobile robot according to the maximum discharge power of the power battery of the autonomous mobile robot specifically include:

[0043] Calculate the maximum mechanical power of the autonomous mobile robot:

[0044] ,

[0045] where is the motor efficiency coefficient, is the transmission efficiency coefficient;

[0046] Configure the target moving speed of the autonomous mobile robot, where is the maximum moving speed of the autonomous mobile robot;

[0047] Calculate the maximum load of the autonomous mobile robot at the target moving speed .

[0048] Furthermore, the steps for calculating the maximum load of the autonomous mobile robot at the target moving speed specifically include:

[0049] Calculate the first mechanical power required for the autonomous mobile robot to overcome its own weight at the target moving speed :

[0050] ,

[0051] where is the rolling friction coefficient of the drive wheels of the autonomous mobile robot on the ground in its working area, is the acceleration due to gravity, is the body weight of the autonomous mobile robot;

[0052] Calculate the second mechanical power for load bearing of the autonomous mobile robot at the target moving speed as follows:

[0053] ;

[0054] Calculate the maximum load of the autonomous mobile robot according to the second mechanical power as follows:

[0055] .

[0056] Furthermore, the steps of matching the items to be loaded in the list of items to be loaded for the autonomous mobile robots in the scheduling queue according to the carrying capacity of each autonomous mobile robot in the scheduling queue specifically include:

[0057] Generate a carrying capacity sequence according to the carrying capacity of each autonomous mobile robot in the scheduling queue, where each element in the carrying capacity sequence is a key-value pair of "carriable volume, carriable weight" corresponding to each autonomous mobile robot in the scheduling queue;

[0058] Determine an item combination for generating a transportation task in the list of items to be loaded at each loading site, so that the sum of the volume and / or weight of the item combination matches one element in the carrying capacity sequence;

[0059] Determine the autonomous mobile robot corresponding to the element in the carrying capacity sequence that matches the item combination as the target autonomous mobile robot.

[0060] Furthermore, the steps of determining an item combination for generating a transportation task in the list of items to be loaded at each loading site, so that the sum of the volume and / or weight of the item combination matches one element in the carrying capacity sequence specifically include:

[0061] Determine a temporary variable and initialize it to ;

[0062] Determine in the list of items to be loaded items to be loaded to form a first temporary item combination and items to be loaded to form a second temporary item combination;

[0063] Calculate the sum of the carrying volumes and the sum of the weights of the first temporary item combination:

[0064] , and

[0065] the sum of the carrying volumes and the sum of the weights of the second temporary item combination:

[0066] ,

[0067] wherein is a positive integer between 1 and ; is the carrying volume of the -th item in the temporary item combination; is the weight of the -th item in the temporary item combination;

[0068] Determine whether the first temporary item combination and the second temporary item combination satisfy:

[0069] , or

[0070] ,

[0071] wherein is a positive integer between 1 and ; is the number of key-value pairs in the carrying capacity sequence; is the carriable volume of the -th key-value pair in the carrying capacity sequence; is the carriable weight of the -th key-value pair in the carrying capacity sequence;

[0072] When the first temporary item combination and the second temporary item combination do not satisfy any of the above conditions, let the temporary variable and then loop to execute to determine unloaded items in the loading item list to form a first temporary item combination and unloaded items in the loading item list to form a second temporary item combination and its subsequent steps.

[0073] The second aspect of the present invention proposes an intelligent scheduling system for an autonomous mobile robot, including:

[0074] A queue construction module for constructing a scheduling queue of the autonomous mobile robot, several loading queues corresponding to the loading sites, and several unloading queues corresponding to the unloading sites;

[0075] A carrying capacity calculation module for recalculating the carrying capacity of the autonomous mobile robot when any one of the autonomous mobile robots enters the idle state;

[0076] A scheduling queue management module for adding the autonomous mobile robot in the idle state to the scheduling queue;

[0077] An item to be loaded list reading module, configured to read the list of items to be loaded corresponding to each loading station, where the list of items to be loaded includes the volume information and weight information of each item to be loaded;

[0078] An item to be loaded matching module, configured to match items to be loaded 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;

[0079] A loading queue management module, configured to move the autonomous mobile robots from the scheduling queue to the loading queue corresponding to the loading station where the matched items to be loaded are located.

[0080] The present invention provides an intelligent scheduling method and system for autonomous mobile robots. By constructing a scheduling queue for autonomous mobile robots, a plurality of loading queues corresponding to loading stations, and a plurality of unloading queues corresponding to unloading stations, 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 station is read, 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 robots are moved from the scheduling queue to the loading queue corresponding to the loading station where the matched items to be loaded are located, which can ensure that the autonomous mobile robots can complete transportation tasks stably and efficiently. Description of the Drawings

[0081] Figure 1 is a flowchart of an intelligent scheduling method for autonomous mobile robots provided by an embodiment of the present invention;

[0082] Figure 2 is a schematic block diagram of an intelligent scheduling system for autonomous mobile robots provided by an embodiment of the present invention. Detailed Embodiments

[0083] In order to more clearly understand the above objects, features and advantages of the present invention, the present invention will be further described in detail below with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0084] Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0085] In the description of the present invention, the term "a plurality of" refers to two or more, unless otherwise clearly defined. The orientation or positional relationship indicated by terms such as "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, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be construed as a limitation of the present invention. Terms such as "connection", "installation", "fixation", etc. should all 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 those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. In addition, terms such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise stated, the meaning of "a plurality of" is two or more.

[0086] In the description of this specification, the descriptions of terms such as "an embodiment", "some embodiments", "specific embodiments", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or instance. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0087] Next, a smart scheduling method and system for an autonomous mobile robot according to some embodiments of the present invention will be described with reference to the drawings.

[0088] As Figure 1 shown, a first aspect of the present invention proposes a smart scheduling method for an autonomous mobile robot, including:

[0089] Construct a scheduling queue for the autonomous mobile robot, several loading queues corresponding to the loading stations, and several unloading queues corresponding to the unloading stations;

[0090] When any autonomous mobile robot enters the idle state, recalculate the carrying capacity of the autonomous mobile robot;

[0091] Add the autonomous mobile robot in the idle state to the scheduling queue;

[0092] Read the list of items to be loaded corresponding to each loading station, and the list of items to be loaded contains the volume information and weight information of each item to be loaded;

[0093] Match the to-be-loaded items in the to-be-loaded item list for the autonomous mobile robots in the scheduling queue according to the carrying capacity of each autonomous mobile robot in the scheduling queue;

[0094] Move the autonomous mobile robot from the scheduling queue to the loading queue corresponding to the loading station where the matched to-be-loaded item is located.

[0095] Specifically, the scheduling queue is a device queue composed of autonomous mobile robots in an idle state. It can be an autonomous mobile robot that enters the idle state after completing the previous work task, or an autonomous mobile robot that enters the idle state after 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 regarded as being in a non-idle state.

[0096] The loading station is a specific location for loading goods or workpieces onto the autonomous mobile robot. It can be one or more pre-designated positions. The loading queue is a device queue composed of autonomous mobile robots queuing at the loading station waiting to be loaded. Therefore, there is a one-to-one correspondence between the loading queue and the loading station. Similarly, the unloading station is a specific location for unloading goods or workpieces from the autonomous mobile robot. It is usually one or more target positions corresponding to the transportation task. The unloading queue is a device queue composed of autonomous mobile robots queuing at the unloading station waiting to be unloaded. Therefore, there is a one-to-one correspondence between the unloading queue and the unloading station.

[0097] The carrying capacity of the autonomous mobile robot is represented by the maximum loadable volume and the maximum loadable weight of the autonomous mobile robot.

[0098] In the to-be-loaded item list, each to-be-loaded item is the smallest unit that can be independently transported. Each to-be-loaded item has a unique number as its unique identity identifier. The to-be-loaded item list is composed of the numbers of all to-be-loaded items in the corresponding loading station.

[0099] Further, the step of moving the autonomous mobile robot from the scheduling queue to the loading queue corresponding to the loading station where the matched to-be-loaded item is located specifically includes:

[0100] Determine the to-be-loaded items matched by the autonomous mobile robot. When there are multiple to-be-loaded items matched by the same autonomous mobile robot, they should belong to the items in the same loading station;

[0101] Determine the station number of the loading station where the item to be loaded matched by the autonomous mobile robot is located;

[0102] Determine the corresponding loading queue number according to the station number;

[0103] Add the autonomous mobile robot to the loading queue corresponding to the loading station number;

[0104] Delete the autonomous mobile robot from the scheduling queue.

[0105] Further, the steps of recalculating the carrying capacity of the autonomous mobile robot specifically include:

[0106] Obtain the open-circuit voltage of the power battery of the autonomous mobile robot and the remaining power ;

[0107] Determine the discharge limit voltage of the power battery of the autonomous mobile robot at the remaining power ; ;

[0108] 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 ;

[0109] According to the maximum discharge power of the power battery of the autonomous mobile robot determine the maximum load of the autonomous mobile robot .

[0110] Specifically, the open-circuit voltage of the power battery of the autonomous mobile robot can be measured by the internal circuit monitoring circuit thereof. The remaining power of the power battery of the autonomous mobile robot is usually presented in the form of a percentage, and the remaining power of the power battery of the autonomous mobile robot can be obtained through the characteristic curve between the open-circuit voltage of the power battery of the autonomous mobile robot and the remaining power . .

[0111] The discharge limit voltage refers to the critical voltage at which the power battery of the autonomous mobile robot corresponding to different remaining power states may cause irreversible damage to the battery if it continues to discharge. The irreversible damage mentioned here includes damage such as performance degradation and shortened lifespan of the power battery of the autonomous mobile robot due to over-discharge.

[0112] The 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 .

[0113] 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:

[0114] Construct an output power constraint model based on the power battery of the autonomous mobile robot:

[0115] ,

[0116] 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;

[0117] Determine the maximum discharge current of the power battery of the autonomous mobile robot using the output power constraint model ;

[0118] Calculate the maximum discharge power of the power battery of the autonomous mobile robot:

[0119] .

[0120] 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.

[0121] 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.

[0122] The characteristic constants in the output power constraint model and is a characteristic constant measured in a laboratory environment for the function relationship between the discharge current and the polarization internal resistance of the power battery that constitutes the autonomous mobile robot. The maximum discharge power of the power battery of the autonomous mobile robot can be analyzed through the output power constraint model .

[0123] Furthermore, the steps of using the output power constraint model to determine the maximum discharge current of the power battery of the autonomous mobile robot specifically include:

[0124] Define a difference function:

[0125] ;

[0126] Construct an iterative calculation model for calculating the maximum discharge current :

[0127] ,

[0128] where is an iterative count variable greater than or equal to 0, and is an integer;

[0129] Iteratively calculate the maximum discharge current based on the iterative calculation model .

[0130] Furthermore, the steps of iteratively calculating the maximum discharge current based on the iterative calculation model specifically include:

[0131] Take the first derivative of the difference function :

[0132] ;

[0133] Initialize the iterative count variable and the initial current ;

[0134] Obtain the pre-configured iterative precision ;

[0135] Use 1 as the iterative step size of the iterative count variable to perform loop iterative calculation:

[0136] ;

[0137] Judge whether the current iteration satisfies:

[0138] ;

[0139] When happens, let the iteration count variable be incremented by 1 and then perform iterative calculation again;

[0140] When happens, assign the maximum discharge current .

[0141] Specifically, the iteration accuracy is a small value pre-configured, which is used as the threshold for the difference between the discharge currents of two iterations and serves as the stop condition for the iterative process. The initial current is a discharge current less than the maximum discharge current , and it 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 initial current , the smaller the difference between it and the maximum discharge current , and the shorter the time required for iteration.

[0142] Furthermore, the steps for determining the maximum load of the autonomous mobile robot according to the maximum discharge power of the power battery of the autonomous mobile robot specifically include:

[0143] Calculate the maximum mechanical power of the autonomous mobile robot:

[0144] ,

[0145] where is the motor efficiency coefficient, is the transmission efficiency coefficient;

[0146] Configure the target moving speed of the autonomous mobile robot, where is the maximum moving speed of the autonomous mobile robot;

[0147] Calculate the maximum load of the autonomous mobile robot at the target moving speed .

[0148] The motor efficiency coefficient represents the efficiency of the motor in converting electrical energy into mechanical energy, while the transmission efficiency coefficient represents the energy transfer efficiency during the transmission process from the motor to the drive wheels. The motor efficiency coefficient and the transmission efficiency coefficient are all measured in a laboratory environment for autonomous mobile robots of the same type. The target moving speed of the autonomous mobile robot is a pre-configured value less than the maximum moving speed of the autonomous mobile robot .

[0149] Furthermore, the steps of calculating the maximum load of the autonomous mobile robot at the target moving speed specifically include:

[0150] Calculating the first mechanical power required for the autonomous mobile robot to overcome its own weight at the target moving speed :

[0151] ,

[0152] where 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;

[0153] Calculating the second mechanical power for the load of the autonomous mobile robot at the target moving speed :

[0154] ;

[0155] Calculating the maximum load of the autonomous mobile robot according to the second mechanical power :

[0156] .

[0157] The rolling friction coefficient is related to the material of the driving wheels of the autonomous mobile robot and the material of the ground in 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 with the material of the driving wheels of the autonomous mobile robot in the workplace is taken as the rolling friction coefficient. The acceleration due to gravity usually takes a value of . The maximum moving speed of the autonomous mobile robot The maximum mechanical power of the autonomous mobile robot is the maximum moving speed when all is used to overcome the friction generated by its own weight, and it satisfies:

[0158] ​ 。

[0159] Further, the step of matching the items to be loaded for the autonomous mobile robots in the scheduling queue in the list of items to be loaded specifically includes:

[0160] Generating a carrying capacity sequence according to the carrying capacity of each autonomous mobile robot in the scheduling queue, where each element in the carrying capacity sequence is a "carriable volume, carriable weight" key-value pair corresponding to each autonomous mobile robot in the scheduling queue;

[0161] Determining an item combination for generating a transportation task in the list of items to be loaded at each loading site, such that the sum of the volume and / or weight of the item combination matches an element in the carrying capacity sequence;

[0162] 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.

[0163] Specifically, the length of the carrying capacity sequence is the same as that of 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 there is a one-to-one correspondence between them. The carriable volume value in each "carriable volume, carriable weight" key-value pair in the carriable volume sequence corresponds to the maximum carriable volume of each autonomous mobile robot in the scheduling queue. Similarly, the carriable weight value in each "carriable volume, carriable weight" key-value pair in the carriable weight sequence corresponds to the maximum carriable weight of each autonomous mobile robot in the scheduling queue.

[0164] Further, in the step of determining an item combination for generating a transportation task in the list of items to be loaded at each loading site, 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 by the corresponding transportation task.

[0165] Further, 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 further includes determining the items to be loaded in the item combination as the items to be loaded matched by the autonomous mobile robot.

[0166] Further, the step of determining an item combination for generating a transportation task in the list of items to be loaded at each loading site, such that the sum of the volume and / or weight of the item combination matches an element in the carrying capacity sequence specifically includes:

[0167] Determine a temporary variable and initialize it to ;

[0168] Determine in the list of items to be loaded items to be loaded to form a first temporary item combination and items to be loaded to form a second temporary item combination;

[0169] Calculate the sum of the carrying volumes and the sum of the weights of the first temporary item combination:

[0170] , and

[0171] the sum of the carrying volumes and the sum of the weights of the second temporary item combination:

[0172] ,

[0173] where is a positive integer between 1 and , is the carrying volume of the th item in the temporary item combination, is the weight of the th item in the temporary item combination;

[0174] Judge whether the first temporary item combination and the second temporary item combination satisfy:

[0175] , or

[0176] ,

[0177] where is a positive integer between 1 and , is the number of key-value pairs in the carrying capacity sequence, is the carriable volume of the th key-value pair in the carrying capacity sequence, is the carriable weight of the th key-value pair in the carrying capacity sequence;

[0178] When the first temporary item combination and the second temporary item combination do not satisfy any of the above conditions, let the temporary variable and then loop to execute determining in the list of items to be loaded items to be loaded to form a first temporary item combination and items to be loaded to form a second temporary item combination and its subsequent steps.

[0179] It should be noted that the carrying volume is not the actual volume of the item to be loaded, but the sum of the actual volume of the item to be loaded and a pre-configured redundancy value, so as to incorporate 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. For items to be loaded with different shapes and materials, the redundancy value is configured with different numerical values.

[0180] The situation where the first temporary item combination and the second temporary item combination do not meet any of the above conditions means that the first temporary item combination and the second temporary item combination do not meet:

[0181] , and do not meet:

[0182] .

[0183] Furthermore, when determining whether the first temporary item combination and the second temporary item combination meet:

[0184] , or

[0185] , the following steps are also included:

[0186] When the first temporary item combination and the second temporary item combination meet one of the above conditions, or both meet, determine the first item combination as the item combination.

[0187] Furthermore, when the first temporary item combination and the second temporary item combination meet , determine the autonomous mobile robots that meet in the scheduling queue to form a first list of autonomous mobile robots;

[0188] Calculate the difference between the carrying volume of each autonomous mobile robot in the first list of autonomous mobile robots and the sum of the carrying volumes of the first temporary item combination:

[0189] ,

[0190] where is a positive integer between 1 and , the number of autonomous mobile robots in the first list of autonomous mobile robots, is the carrying volume of the th autonomous mobile robot in the first list of autonomous mobile robots;

[0191] Determine a target autonomous mobile robot in the first list of autonomous mobile robots such that the target autonomous mobile robot meets:

[0192] ,

[0193] wherein is the loadable volume of the target autonomous mobile robot.

[0194] Further, when the first temporary item combination and the second temporary item combination satisfy determine, in the scheduling queue, the autonomous mobile robots that satisfy to form a second list of autonomous mobile robots;

[0195] Calculate the difference between the loadable weight of each autonomous mobile robot in the second list of autonomous mobile robots and the sum of the load weights of the first temporary item combination:

[0196] ,

[0197] wherein is a positive integer between 1 and , is the number of autonomous mobile robots in the second list of autonomous mobile robots, is the loadable weight of the th autonomous mobile robot in the first list of autonomous mobile robots;

[0198] Determine a target autonomous mobile robot in the second list of autonomous mobile robots such that the target autonomous mobile robot satisfies:

[0199] ,

[0200] wherein is the loadable weight of the target autonomous mobile robot.

[0201] As Figure 2 shown, a second aspect of the present invention provides an intelligent scheduling system for an autonomous mobile robot, including:

[0202] A queue construction module for constructing a scheduling queue of autonomous mobile robots, a plurality of loading queues corresponding to loading sites, and a plurality of unloading queues corresponding to unloading sites;

[0203] A load capacity calculation module for recalculating the load capacity of an autonomous mobile robot when any autonomous mobile robot enters an idle state;

[0204] A scheduling queue management module for adding the autonomous mobile robots in the idle state to the scheduling queue;

[0205] The to-be-loaded item list reading module is used to read the to-be-loaded item list corresponding to each loading station, and the to-be-loaded item list contains the volume information and weight information of each to-be-loaded item;

[0206] The to-be-loaded item matching module is used to match the to-be-loaded items in the to-be-loaded item list for the autonomous mobile robots in the scheduling queue according to the carrying capacity of each autonomous mobile robot in the scheduling queue;

[0207] The loading queue management module is used to move the autonomous mobile robots from the scheduling queue to the loading queue corresponding to the loading station where the matched to-be-loaded items are located.

[0208] Specifically, the scheduling queue is a device queue composed of autonomous mobile robots in an idle state. It can be an autonomous mobile robot that enters the idle state after completing the previous work task, or an autonomous mobile robot that enters the idle state after 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 regarded as being in a non-idle state.

[0209] The loading station is a specific location for loading goods or workpieces onto the autonomous mobile robot. It can be one or more pre-specified positions. The loading queue is a device queue composed of autonomous mobile robots queuing at the loading station waiting to be loaded. Therefore, the loading queue has a one-to-one correspondence with the loading station. Similarly, the unloading station is a specific location for unloading goods or workpieces from the autonomous mobile robot. It is usually one or more target positions corresponding to the transportation task. The unloading queue is a device queue composed of autonomous mobile robots queuing at the unloading station waiting to be unloaded. Therefore, the unloading queue has a one-to-one correspondence with the unloading station.

[0210] The carrying capacity of the autonomous mobile robot is represented by the maximum loadable volume and the maximum loadable weight of the autonomous mobile robot.

[0211] In the to-be-loaded item list, each to-be-loaded item is the smallest unit that can be independently transported. Each to-be-loaded item has a unique number as its unique identity identifier, and the to-be-loaded item list is composed of the numbers of all to-be-loaded items in the corresponding loading station.

[0212] Furthermore, the loading queue management module specifically includes:

[0213] An item to be loaded determination module, configured to determine the item to be loaded that matches the autonomous mobile robot. When there are multiple items to be loaded that match the same autonomous mobile robot, they should belong to the items at the same loading station;

[0214] A station number determination module, configured to determine the station number of the loading station where the item to be loaded that matches the autonomous mobile robot is located;

[0215] A loading queue number determination module, configured to determine the corresponding loading queue number according to the station number;

[0216] An autonomous mobile robot addition module, configured to add the autonomous mobile robot to the loading queue corresponding to the loading station number;

[0217] An autonomous mobile robot deletion module, configured to delete the autonomous mobile robot from the scheduling queue.

[0218] Further, the carrying capacity calculation module specifically includes:

[0219] A battery parameter acquisition module, configured to acquire the open-circuit voltage of the power battery of the autonomous mobile robot and the remaining battery level ;

[0220] A discharge limit voltage determination module, configured to determine the discharge limit voltage of the power battery of the autonomous mobile robot at the remaining battery level ; ;

[0221] A maximum discharge power calculation module, configured to calculate the maximum discharge power of the power battery of the autonomous mobile robot according to the open-circuit voltage and the discharge limit voltage ; ;

[0222] A maximum load determination module, configured to determine the maximum load of the autonomous mobile robot according to the maximum discharge power of the power battery of the autonomous mobile robot ; ;

[0223] Specifically, the open-circuit voltage of the power battery of the autonomous mobile robot can be measured by an internal circuit monitoring circuit thereof. The remaining battery level of the power battery of the autonomous mobile robot is usually presented in the form of a percentage. The remaining battery level of the power battery of the autonomous mobile robot can be obtained through the characteristic curve between the open-circuit voltage and the remaining battery level ; 。

[0224] The discharge limit voltage refers to the critical voltage at which the power battery of the autonomous mobile robot, corresponding to different remaining battery levels, may cause irreversible damage to the battery if it continues to discharge. The irreversible damage mentioned here includes damage such as a decrease in the performance and shortening of the lifespan of the power battery of the autonomous mobile robot due to over-discharge.

[0225] The discharge limit voltage of the power battery of the autonomous mobile robot shows different values under different remaining battery levels. At the same time, when using different types of power batteries, the discharge limit voltages at each remaining battery level will vary. In the technical solution of the present invention, the power battery of the autonomous mobile robot at the discharge limit voltage at the remaining battery level is measured through a large number of experimental tests on the same type of battery in a laboratory environment. For each percentage value of the remaining battery level , there will be a pre-measured and configured discharge limit voltage 。

[0226] Furthermore, the maximum discharge power calculation module specifically includes:

[0227] An output power constraint model construction module, used to construct an output power constraint model based on the power battery of the autonomous mobile robot:

[0228] ,

[0229] where 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 are the characteristic constants of the power battery of the autonomous mobile robot;

[0230] A maximum discharge current determination module, used to determine the maximum discharge current of the power battery of the autonomous mobile robot using the output power constraint model ;

[0231] 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:

[0232] 。

[0233] Specifically, the ohmic internal resistance of the power battery of the autonomous mobile robot It is a part of the internal resistance of the power battery, with a relatively fixed resistance value and is independent of the discharge current of the power battery.

[0234] In the technical solution of the above embodiment, the output power constraint model is a simplified model for characterizing the functional relationship between the open-circuit voltage of the power battery of the autonomous mobile robot and its discharge current.

[0235] The characteristic constants in the output power constraint model and are characteristic constants measured in a laboratory environment for constituting the functional relationship between the discharge current and the polarization internal resistance of the power battery of the autonomous mobile robot. Through the output power constraint model, the maximum discharge power of the power battery of the autonomous mobile robot can be analyzed .

[0236] Furthermore, the maximum discharge current determination module specifically includes:

[0237] A difference function definition module for defining a difference function:

[0238] ;

[0239] An iterative calculation model construction module for constructing an iterative calculation model for calculating the maximum discharge current :

[0240] ,

[0241] where is an iterative counting variable greater than or equal to 0, and is an integer;

[0242] The maximum discharge current determination module is specifically configured to iteratively calculate the maximum discharge current based on the iterative calculation model .

[0243] Furthermore, the maximum discharge current determination module further includes:

[0244] A first-order derivative calculation module for performing a first-order derivative on the difference function :

[0245] ;

[0246] An iterative parameter initialization module for initializing the iterative counting variable and the initial current ;

[0247] An iterative precision acquisition module for acquiring a pre-configured iterative precision ;

[0248] A cyclic iteration calculation module for performing cyclic iteration calculations with 1 as the iteration count variable and an iteration step size of:

[0249] ;

[0250] An iteration condition judgment module for judging whether the current iteration satisfies:

[0251] ;

[0252] Specifically, the cyclic iteration calculation module is used to, when , increment the iteration count variable by 1 and then perform iteration calculations again;

[0253] A maximum discharge current assignment module for assigning the maximum discharge current when .

[0254] Specifically, the iteration accuracy is a relatively small value pre-configured, which is used as the threshold for the difference between the discharge currents of two iterations and serves as the stop condition for the iteration process. The initial current is a discharge current less than the maximum discharge current , and it 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 initial current , the smaller the difference between it and the maximum discharge current , and the shorter the time required for iteration.

[0255] Furthermore, the maximum load determination module specifically includes:

[0256] A maximum mechanical power calculation module for calculating the maximum mechanical power of the autonomous mobile robot:

[0257] ,

[0258] where is the motor efficiency coefficient, is the transmission efficiency coefficient;

[0259] A target moving speed configuration module for configuring the target moving speed of the autonomous mobile robot, where The maximum moving speed of the autonomous mobile robot;

[0260] The maximum load determination module is specifically configured to calculate the maximum load of the autonomous mobile robot at the target moving speed under the target moving speed .

[0261] The motor efficiency coefficient represents the efficiency of the motor in converting electrical energy into mechanical energy, while the transmission efficiency coefficient represents the energy transfer efficiency during the transmission process from the motor to the drive wheels. The motor efficiency coefficient and the transmission efficiency coefficient are both measured in a laboratory environment for autonomous mobile robots of the same type. The target moving speed of the autonomous mobile robot is a pre-configured value less than the maximum moving speed of the autonomous mobile robot.

[0262] Further, the maximum load determination module further includes:

[0263] A first mechanical power calculation module, configured to calculate the first mechanical power required for the autonomous mobile robot to overcome its own weight at the target moving speed under the target moving speed:

[0264] ,

[0265] where is the rolling friction coefficient of the drive 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;

[0266] A second mechanical power calculation module, configured to calculate the second mechanical power for carrying the load of the autonomous mobile robot at the target moving speed under the target moving speed:

[0267] ;

[0268] The maximum load determination module is specifically configured to calculate the maximum load of the autonomous mobile robot according to the second mechanical power :

[0269] .

[0270] The rolling friction coefficient It is related to the material of the driving wheels of the autonomous mobile robot and the material of the ground in 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 force between the driving wheels of the autonomous mobile robot in the workplace is taken as the rolling friction coefficient. . The gravitational acceleration Generally takes the value of . The maximum moving speed of the autonomous mobile robot The maximum mechanical power of the autonomous mobile robot When all is used to overcome the frictional force generated by its own weight, the maximum moving speed, which satisfies:

[0271] .

[0272] Further, the item loading matching module specifically includes:

[0273] A carrying capacity sequence generation module, which is used to generate a carrying capacity sequence according to the carrying capacity of each autonomous mobile robot in the scheduling queue. Each element in the carrying capacity sequence is a key-value pair of "carriable volume, carriable weight" corresponding to each autonomous mobile robot in the scheduling queue;

[0274] An item combination determination module, which is used to determine an item combination for generating a transportation 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 carrying capacity sequence;

[0275] A target autonomous mobile robot determination module, which is used to determine the autonomous mobile robot corresponding to the element in the carrying capacity sequence that matches the item combination as the target autonomous mobile robot.

[0276] Specifically, the length of the carrying capacity sequence is the same as that of 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 there is a one-to-one correspondence between the two. The carriable volume value in each "carriable volume, carriable weight" key-value pair in the carriable volume sequence corresponds to the maximum carriable volume of each autonomous mobile robot in the scheduling queue. Similarly, the carriable weight value in each "carriable volume, carriable weight" key-value pair in the carriable weight sequence corresponds to the maximum carriable weight of each autonomous mobile robot in the scheduling queue.

[0277] Further, in the item combination determination module, 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 by the corresponding transportation task.

[0278] Further, the to-be-loaded item matching module is further configured to determine the to-be-loaded items matched by the autonomous mobile robot from the to-be-loaded items in the item combination.

[0279] Further, the item combination determining module specifically includes:

[0280] A temporary variable initialization module, configured to determine a temporary variable and initialize it to ;

[0281] A temporary item combination generation module, configured to determine to-be-loaded items from the loading item list to form a first temporary item combination and to-be-loaded items to form a second temporary item combination;

[0282] A volume and weight accumulation module, configured to calculate the sum of the carrying volumes and the sum of the weights of the first temporary item combination:

[0283] , and

[0284] the sum of the carrying volumes and the sum of the weights of the second temporary item combination:

[0285] ,

[0286] where is a positive integer between 1 and , is the carrying volume of the th item in the temporary item combination, is the weight of the th item in the temporary item combination;

[0287] A boundary judgment module, configured to judge whether the first temporary item combination and the second temporary item combination satisfy:

[0288] , or

[0289] ,

[0290] where is a positive integer between 1 and , is the number of key-value pairs in the carrying capacity sequence, is the carriable volume of the th key-value pair in the carrying capacity sequence, is the carriable weight of the th key-value pair in the carrying capacity sequence;

[0291] A loop execution module, configured to, when the first temporary item combination and the second temporary item combination do not meet any of the above conditions, make the temporary variable subsequently loop to execute to determine in the list of items to be loaded a number of items to be loaded to form a first temporary item combination and a number of items to be loaded to form a second temporary item combination and subsequent steps.

[0292] 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 incorporate the volume occupied by the gaps between the multiple items to be loaded when placed on the loading tray of the autonomous mobile robot into the calculation. For items to be loaded with different shapes and materials, the redundancy value is configured with different numerical values.

[0293] The fact that the first temporary item combination and the second temporary item combination do not meet any of the above conditions means that the first temporary item combination and the second temporary item combination do not meet:

[0294] , and do not meet:

[0295] Furthermore, the item combination determination module is further configured to, when the first temporary item combination and the second temporary item combination meet one of the above conditions, or both meet, determine the first item combination as the item combination.

[0296] Furthermore, the item combination determination module further includes:

[0297] A first autonomous mobile robot list generation module, configured to, when the first temporary item combination and the second temporary item combination meet , determine, in the scheduling queue, the autonomous mobile robots that meet to form a first autonomous mobile robot list;

[0298] A first difference calculation module, configured 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 volume of the first temporary item combination:

[0299] ,

[0300] where is a positive integer between 1 and , the number of autonomous mobile robots in the first autonomous mobile robot list, is the loadable volume of the

[0301] The target autonomous mobile robot determination module is specifically configured to determine a target autonomous mobile robot in the first list of autonomous mobile robots, such that the target autonomous mobile robot satisfies:

[0302] ,

[0303] where is the loadable volume of the target autonomous mobile robot.

[0304] Further, the item combination determination module further includes:

[0305] A second list generation module for autonomous mobile robots, configured to determine, in the scheduling queue, autonomous mobile robots that satisfy when the first temporary item combination and the second temporary item combination satisfy to form a second list of autonomous mobile robots;

[0306] A second difference calculation module, configured to calculate the difference between the loadable weight of each autonomous mobile robot in the second list of autonomous mobile robots and the sum of the load weights of the first temporary item combination:

[0307] ,

[0308] where is a positive integer between 1 and , is the number of autonomous mobile robots in the second list of autonomous mobile robots, is the loadable weight of the th autonomous mobile robot in the first list of autonomous mobile robots;

[0309] The target autonomous mobile robot determination module is specifically configured to determine a target autonomous mobile robot in the second list of autonomous mobile robots, such that the target autonomous mobile robot satisfies:

[0310] ,

[0311] where is the loadable weight of the target autonomous mobile robot.

[0312] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the existence of additional identical elements in the process, method, article or device comprising said element.

[0313] As described above in accordance with the embodiments of the present invention, 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 variations can be made according to the above description. These embodiments are selected and specifically described in this specification 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 its modifications based on the present invention. The present invention is only limited 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; Moving the autonomous mobile robot from the dispatch queue to a loading queue corresponding to a loading station where the matched object to be loaded is located; 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 , the maximum load The autonomous mobile robot moves at a pre-configured target speed Maximum load under load; 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 , is the maximum moving speed of the autonomous mobile robot; Calculate the target moving speed of the autonomous mobile robot Maximum load under .

2. The intelligent scheduling method for an autonomous mobile robot according to claim 1, 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: 。 3. The intelligent scheduling method for an autonomous mobile robot according to claim 2, 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 .

4. The intelligent scheduling method for an autonomous mobile robot according to claim 3, 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 .

5. The intelligent scheduling method for an autonomous mobile robot according to claim 1, 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: 。 6. The intelligent scheduling method for an autonomous mobile robot according to claim 1, 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.

7. The intelligent scheduling method for an autonomous mobile robot according to claim 6, 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.

8. 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; A loading queue management module, used to move 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; 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 , the maximum load The autonomous mobile robot moves at a pre-configured target speed Maximum load under load; 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 , is 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 .

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