Swarm machine autonomous system and method

Abstract

This application provides a group machine autonomous system and method. The group machine autonomous system includes a group machine core and at least one group machine fleet, the at least one group machine fleet including at least one group machine agent, wherein: the group machine core is configured to manage the group machine autonomous system and generate a group machine plan and a first configuration of the group machine plan, wherein the first configuration is configured as a set of group machine roles and relationships in production operations; and the group machine fleet is configured to execute the production operations according to the group machine plan.

Description

Technical Field

[0001] This application relates to the field of production technology, and in particular to a group-machine autonomous system and method. Background Technology

[0002] With the development of production technology, production environments are becoming increasingly complex. To coordinate industrial robots involved in the production process, heterogeneous group management is often used to manage different types of industrial robot groups. However, current heterogeneous group management has relatively low flexibility and faces some challenges in adapting to complex industrial production environments. Summary of the Invention

[0003] In view of this, it is necessary to provide a swarm autonomous system and method.

[0004] In a first aspect, one embodiment of this application provides a swarm autonomous system for industrial applications, the swarm autonomous system comprising a swarm core and at least one swarm vehicle fleet, the at least one swarm vehicle fleet comprising at least one swarm agent, wherein:

[0005] The cluster core is configured to manage the cluster autonomous system and generate cluster plans and a first configuration for the cluster plans, wherein the first configuration is configured as a set of cluster roles and relationships in production operations; and

[0006] The fleet of aircraft is configured to perform the production operations according to the fleet schedule.

[0007] In one possible implementation of this application, the at least one fleet of vehicles further includes at least one fleet of workpieces;

[0008] The swarm core is further configured to generate a second configuration for the at least one swarm vehicle fleet and swarm participants therein, wherein the swarm participants include swarm agents and swarm artifacts.

[0009] In one possible implementation of this application, the cluster core communicates with the at least one cluster agent and the at least one cluster workpiece via a cluster protocol, wherein the cluster protocol transmits operating data, planning data, monitoring data, and configuration data among the cluster core, the at least one cluster agent, and the at least one cluster workpiece.

[0010] In one possible implementation of this application, the cluster protocol includes a Quality of Service (QoS) policy, wherein the QoS policy is configured to define the network requirements for the runtime data, the planning data, the monitoring data, and the configuration data.

[0011] In one possible implementation of this application, the cluster core is further configured to avoid cluster failures, wherein the cluster failures include participant failures, operational failures, and network failures.

[0012] In one possible implementation of this application, the autonomous system for swarm aircraft further includes a swarm aircraft decision group, wherein the swarm aircraft decision group is defined as a subgroup of the swarm aircraft fleet, and the swarm aircraft decision group is configured to perform the production operation in adverse execution scenarios or network conditions.

[0013] In one possible implementation of this application, the group machine resolution group further includes a group leader configured to exchange execution information with at least one group machine member outside the group machine resolution group, wherein the at least one group machine member includes the group machine core, the at least one group machine agent, and the at least one group machine artifact.

[0014] In one possible implementation of this application, the communication between at least one group member within the group decision group is configured as a distributed topology.

[0015] In one possible implementation of this application, the swarm machine plan includes task sorting, task prediction, and task recalculation;

[0016] The task sorting includes a list of tasks for the production operation, and the task sorting also includes the relationships between tasks;

[0017] The task prediction includes subsequent tasks ordered according to the task; and

[0018] The task recalculation is configured to perform task rescheduling and task re-prediction after a fault is detected.

[0019] In one possible implementation of this application, the swarm autonomous system further includes a swarm protocol encapsulator, wherein the swarm protocol encapsulator is connected to the swarm core, the at least one swarm agent, and the at least one swarm artifact, and the swarm protocol encapsulator is configured to convert its original protocol into the swarm protocol.

[0020] Secondly, one embodiment of this application provides a swarm autonomous system method applied to a swarm autonomous system, the swarm autonomous system including a swarm core and at least one swarm vehicle fleet, the at least one swarm vehicle fleet including at least one swarm agent, wherein the method includes:

[0021] Manage the autonomous cluster system and generate a cluster plan and a first configuration of the cluster plan, wherein the first configuration is configured as a set of cluster roles and relationships in production operations;

[0022] The fleet of aircraft is configured to perform the production operations according to the fleet plan, and the production operations involve scenarios involving perception, collaboration, and dynamic configuration.

[0023] In one possible implementation of this application, the at least one fleet of vehicles further includes at least one fleet of workpieces;

[0024] Generate a second configuration of the at least one swarm vehicle fleet and swarm vehicle participants therein, wherein the swarm vehicle participants include swarm vehicle agents and swarm vehicle artifacts.

[0025] In one possible implementation of this application, the method further includes:

[0026] Define the cluster machine awareness of the production operation scenario, which is achieved through cluster machine protocol, quality of service, and avoidance of cluster machine failures;

[0027] Determine whether the group machine perception is implemented;

[0028] Define the group machine collaboration in the production operation scenario, wherein the group machine collaboration is achieved by defining group machine roles, capabilities, and group machine plans;

[0029] Determine whether the group machine collaboration is achieved;

[0030] If the aforementioned cluster collaboration is achieved, then a cluster dynamic configuration process is defined, which is implemented by deploying the configuration of the cluster solution;

[0031] Determine whether the dynamic configuration process for the cluster machines has been implemented;

[0032] If the dynamic configuration process of the cluster machines is completed, the deployment of the autonomous cluster machine system is finished.

[0033] In one possible implementation of this application, the cluster sensing is further implemented through a cluster protocol encapsulator, wherein the cluster protocol encapsulator is connected to the cluster core, the at least one cluster agent, or the at least one cluster artifact, and the cluster protocol encapsulator is configured to translate its original protocol into the cluster protocol.

[0034] In one possible implementation of this application, the method further includes:

[0035] The system communicates with at least one cluster agent and at least one cluster artifact via a cluster protocol, wherein the cluster protocol is configured to transfer operational data, planning data, monitoring data, and configuration data between the cluster core, at least one cluster agent, and at least one cluster artifact.

[0036] In one possible implementation of this application, the cluster protocol includes a quality of service policy, wherein the quality of service policy is configured as the running data, the planning data, the monitoring data, and the configuration data network requirements.

[0037] In one possible implementation of this application, the method further includes:

[0038] To avoid cluster machine failures, wherein the cluster machine failures include participant failures, operational failures, and network failures.

[0039] In one possible implementation of this application, the method further includes:

[0040] A group of machine decision groups is set up, wherein the group of machine decision groups is defined as a subgroup of the group of machine fleets, and the group of machine decision groups is configured to perform the production operation in adverse execution scenarios or network conditions.

[0041] In one possible implementation of this application, the method further includes:

[0042] A group of leaders is set up within the group machine resolution group, wherein the group leaders are configured to exchange execution information with at least one group machine member outside the group machine resolution group, wherein the at least one group machine member includes the group machine core, the at least one group machine agent, and the at least one group machine artifact.

[0043] In one possible implementation of this application, the method further includes:

[0044] The communication between at least one group member within the group decision group is configured as a distributed topology.

[0045] In one possible implementation of this application, the method further includes:

[0046] Generate a task sort, wherein the task sort includes a list of tasks for the production operation, and the task sort also includes the relationships between tasks;

[0047] Generate a task prediction, wherein the task prediction includes subsequent tasks ordered according to the task; and

[0048] A task recalculation is generated, wherein the task recalculation is configured to perform task rescheduling and task re-prediction after a fault is detected.

[0049] The autonomous swarm system and method provided in this application can realize the perception, cooperation and dynamic configuration capabilities of the autonomous swarm system. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of a swarm autonomous system provided in an embodiment of this application.

[0051] Figure 2 This is a schematic diagram of a swarm autonomous system provided in another embodiment of this application.

[0052] Figure 3 This is a schematic diagram of a swarm autonomous system provided in another embodiment of this application.

[0053] Figure 4 This is a schematic diagram of a swarm autonomous system provided in another embodiment of this application.

[0054] Figure 5 This is a flowchart illustrating a group-machine autonomous method provided in an embodiment of this application.

[0055] Figure 6 This is a flowchart illustrating a group-machine autonomous method provided in another embodiment of this application.

[0056] The following detailed description, in conjunction with the accompanying drawings, will further illustrate this application. Detailed Implementation

[0057] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0058] It should be noted that, in the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application.

[0059] It should be noted that in the embodiments of this application, the terms "first," "second," etc., are used only for descriptive purposes and should not be construed as indicating or implying relative importance, nor as indicating or implying order. Features specified as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0060] Based on the embodiments described in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0061] The following detailed description of some embodiments of the application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0062] Figure 1 This application provides a cluster autonomous system 10 according to one embodiment. The cluster autonomous system 10 is connected to environmental participants 20. Environmental participants 20 include all physical elements in the production environment that cannot be controlled by the cluster autonomous system 10 as part of it. In one embodiment, environmental participants 20 include factory goods, operators and their locations, and building features.

[0063] The autonomous cluster system 10 is a system with sensing, collaboration, and dynamic configuration capabilities. Cluster sensing in production execution scenarios is achieved through cluster protocols and quality of service (QoS) policies. The QoS policies are related to the transmission time, frequency, and acceptable value range of relevant information. Collaboration is related to the contribution of each cluster participant. The contributions of cluster participants are defined through capabilities, cluster roles, and cluster failure avoidance processes. Dynamic configuration relates to the autonomous cluster system 10's ability to adjust the system topology based on feedback information.

[0064] In this embodiment, the autonomous swarm system 10 includes a swarm core 100 and at least one swarm vehicle fleet 200.

[0065] The cluster core 100 is a software platform that can be executed by any hardware device. The hardware device meets the specific computing or network connectivity requirements of the cluster autonomous system 10.

[0066] The cluster core 100 manages at least one cluster fleet 200. The cluster core 100 includes at least one cluster fleet manager 110. Each cluster fleet manager 110 is configured to manage one cluster fleet 200. The cluster fleet manager 110 is configured as a software module or hardware unit based on the architecture of the cluster core 100.

[0067] In this embodiment, the swarm robot fleet 200 includes at least one swarm robot agent 210 and at least one swarm robot workpiece 220. The swarm robot agent 210 comprises all the robots in the swarm robot autonomous system 10. These robots may differ at the hardware or software level. The swarm robot agent 210 can communicate via a swarm robot protocol 31 (e.g., ...). Figure 2 (As shown) Transmit or receive data. Cluster agent 210 follows and executes cluster plan 120 (e.g.) Figure 3 (As shown).

[0068] Group machine workpiece 220 comprises all devices in the group machine autonomous system 10 except for the robots. These devices may differ at the hardware or software level. Group machine workpiece 220 can communicate via group machine protocol 31 (e.g., ...). Figure 2 (As shown) Transmit or receive data. Group machine workpiece 220 follows and executes group machine plan 120 (e.g.) Figure 3 (As shown).

[0069] The group vehicle fleet management system 110 is easy to deploy and is used to manage group vehicle agents 210 and group vehicle artifacts 220. The group vehicle fleet management system 110 is also configured to manage a group vehicle resolution group 230 (e.g., ...). Figure 2 (As shown). Among them, the cluster resolution group 230 is defined by the cluster core 100. The cluster resolution group 230 can be defined by a set of configuration user interfaces (UI) or configuration tools.

[0070] Figure 2 A swarm autonomous system (swarm autonomous system 10a) according to another embodiment of this application is illustrated. The swarm autonomous system 10a includes a swarm core 100 and at least one swarm vehicle fleet 200a. The core 100 manages the swarm vehicle fleet 200a. Figure 2 As shown, the difference between the autonomous group system 10a and the autonomous group system 10 is that the autonomous group system 10a also includes a group network 30, and the group vehicle fleet 200a also includes a group decision group 230.

[0071] like Figure 2 As shown, in this embodiment, the cluster network 30 includes a cluster protocol 31. The cluster resolution group 230 includes a group leader 231, a cluster network 240, at least one cluster agent 210, and at least one cluster artifact 220. The cluster network 240 includes the cluster protocol 31. The group leader 231 is configured to interact with at least one cluster artifact outside the cluster resolution group 230 to exchange production information. The at least one cluster artifact includes a cluster core 100, at least one cluster agent 210, and at least one cluster artifact 220.

[0072] In this embodiment, the devices in the autonomous swarm system 10a interact based on the swarm protocol 31 in the swarm network 30. The swarm network 30 connects the swarm core 100 and the swarm vehicle fleet 200a. The swarm network 30 enables the swarm core 100 and the swarm vehicle fleet 200a to exchange data based on the swarm protocol 31. The data types defined in the swarm protocol 31 are shown below.

[0073] Operational data: The operational data is the production data generated by the cluster machine core 100. The operational data is used to control the cluster machine agent 210 and the cluster machine workpiece 220 to perform operations.

[0074] Planning data: The planning data is generated by specific types of group machine workpieces 220 according to systems such as Manufacturing Execution System (MES), Enterprise Resource Planning (ERP), or Warehouse Management System (WMS). The planning data controls the group machine core 100 to generate corresponding operational data. In this embodiment, the planning data is data related to planning requirements, resource allocation, and execution organization.

[0075] Monitoring data: The monitoring data is generated by a specific type of group machine workpiece 220 when monitoring any group machine participant. The monitoring data defines all information related to equipment status, manufacturing operations, and the environment.

[0076] Configuration data: The configuration data is generated by a specific type of cluster workpiece 220. The configuration data is used to define the parameters of each cluster agent 210, cluster workpiece 220, and cluster core 100 in the cluster autonomous system 10a. The configuration data can be transferred between the cluster core 100, cluster agent 210, and cluster workpiece 220.

[0077] The cluster protocol 31 also includes Quality of Service (QoS) 32. The cluster protocol 31 sets different QoS 32 policies based on the network requirements of operational data, planning data, monitoring data, and configuration data. The network requirements set by QoS 32 include, but are not limited to, throughput, latency, and packet loss rate requirements. For example, the cluster protocol 31 can set a QoS 32 policy with zero packet loss rate and low throughput for monitoring data. The cluster protocol 31 can also set a QoS 32 policy with low packet loss rate and high throughput for operational data.

[0078] Data interaction under the Cluster Protocol 31 can be either proactive or reactive. Data can be shared from one cluster participant to another, regardless of whether the other participant initiates an interaction request. Proactive data interaction can occur in a timed mode or be triggered by a task. Reactive data interaction requires the other participant to issue a specific interaction request to trigger the data interaction. The data interaction process implemented through Cluster Protocol 31 is described as data domain interaction, while the data interaction implemented using cluster fault avoidance strategies is described as secure interaction. Applying Cluster Protocol 31 between the cluster core 100, cluster agent 210, and cluster artifact 220 ensures awareness within cluster autonomy.

[0079] The autonomous cluster system 10 is a hybrid distributed system. It can switch between centralized and distributed topologies based on production scenarios and network conditions. When in a centralized topology, all cluster agents 210 and cluster artifacts 220 are directly managed by the cluster core 100. Under normal production scenarios and network conditions, the autonomous cluster system 10 exhibits a centralized topology. All cluster agents 210 and cluster artifacts 220 need to transmit data to the cluster core 100. The cluster core 100 directly sends production information to either the cluster agents 210 or the cluster artifacts 220. Using a centralized topology reduces the overall communication overhead of the autonomous cluster system 10.

[0080] When the autonomous group system 10a is in a distributed topology, it can select specific group agents 210 and group artifacts 220 within the group vehicle fleet 200a to establish a group decision group 230 based on the production scenario and network conditions. The group decision group 230 is a subgroup within the group vehicle fleet 200a. The group decision group 230 is configured to perform production operations under unfavorable production scenarios or network conditions. Communication between at least one group participant within the group decision group 230 is configured in a distributed topology.

[0081] Group decision group 230 selects either group agent 210 or group workpiece 220 as group leader 231. Within group decision group 230, group leader 231 transmits operational information to group agents 210 or group workpieces 220 outside group decision group 230. Group leader 231 receives operational information from outside group decision group 230. Group leader 231 then sends the corresponding information to group agents 210 or group workpieces 220 within group decision group 230 based on the type of received operational information. Within group decision group 230, group agents 210 and group workpieces 220, excluding group leader 231, are in a distributed topology. Group agents 210 and group workpieces 220 of group decision group 230 can utilize the operational information to execute production tasks.

[0082] The cluster core 100 can be used to prevent cluster failures. The method for preventing cluster failures is also known as a fail-safe strategy. The cluster core 100 detects participant failures, operational failures, and network failures via the cluster protocol 31. These participant failures, operational failures, or network failures may be caused by erroneous computations or communication failures. The cluster core 100 can determine different types of cluster failures using the cluster protocol 31 and execute corresponding recovery methods. The types of cluster failures are as follows.

[0083] Participant Failure: The cluster core 100 can detect failures in cluster participants via cluster protocol 31. Failures in cluster participants may be caused by failure events. Failure events include, but are not limited to, the sudden shutdown or disconnection of the cluster agent 210. Failures in cluster participants can be adjusted and recovered through cluster task recalculation.

[0084] Operational Fault: The autonomous group system 10a can detect computational faults in the group core 100 according to the group protocol 31. These faults may be caused by fault events. Fault events include, but are not limited to, the centralized data computation in the group core 100 reaching a bottleneck. Upon detecting an operational fault, the autonomous group system 10a can establish at least one group decision group 230. The group agent 210 and group workpiece 220 in the group decision group 230 take over the computation within the group vehicle fleet 200a, which reduces data computation in the group core 100.

[0085] Network Failure: The cluster core 100 can detect network failures via cluster protocol 31. Network failures may be caused by network coverage limitations or network congestion. The cluster autonomous system 10a can establish at least one cluster resolution group 230 to avoid network failures. Transmitting operational data within the cluster resolution group 230 can distribute or redistribute network load and bridge data from cluster participants outside network coverage.

[0086] Applying swarm protocol 31 among swarm participants ensures the awareness of the swarm autonomous system 10a. Awareness ensures that swarm participants within the swarm autonomous system 10a can utilize the information provided by awareness.

[0087] Figure 3 A swarm autonomous system 10b according to another embodiment of this application is shown. The swarm autonomous system 10b includes a swarm core 100 and at least a swarm of vehicles 200. The swarm core 100 includes a swarm planning 120, and the swarm planning 120 includes a task sequencing 121.

[0088] The cluster core 100 is configured as the first configuration for generating the cluster plan 120. This first configuration is set up to define a series of cluster roles and relationships during production. Cluster roles include a set of capability requirements that cluster agents 210 or cluster workpieces 220 need to meet when performing production operations.

[0089] The cluster core 100 is also configured to generate a second configuration of cluster fleet 200 and cluster participants. Cluster participants include cluster agents 210 and cluster artifacts 220 within the cluster fleet 200.

[0090] Numerous tasks exist in the industrial product manufacturing process. To improve the efficiency of industrial production, it is necessary to add timing to these tasks. In the swarm autonomous system 10b, tasks can be completed quickly through task planning, task prediction, and task recalculation. The swarm autonomous system 10b includes swarm planning 120 to plan tasks. Swarm planning 120 includes task sequencing 121, task prediction, and task rescheduling.

[0091] Task sequencing 121 is a series of production tasks in the swarm autonomous system 10b. For example, task sequencing 121 can be a sequence of tasks to be executed based on planning data. Task sequencing 121 includes a sequence of tasks to be executed and may include multiple tasks.

[0092] Task prediction includes tasks related to task sequencing 121. Task sequencing 121 also includes temporal or conditional relationships between tasks. The swarm autonomous system 10b performs task prediction based on these relationships and allocates resources accordingly. The swarm plan 120 can generate auxiliary preparation tasks for the swarm core 100, swarm agent 210, and swarm artifact 220 based on task prediction, so that tasks can be executed immediately upon receipt.

[0093] Task recalculation: After a fault is detected via the cluster protocol 31, the cluster autonomous system 10b performs task reordering and task re-prediction based on task recalculation.

[0094] Applying task planning 120 ensures production and enables collaboration within the autonomous swarm system 10b. Collaborative autonomy within the swarm system ensures the collective benefit of the autonomous swarm system 10b during production operations.

[0095] Figure 4 This application illustrates a swarm autonomous system provided by another embodiment of the present application.

[0096] Figure 4 The deployment of the autonomous swarm system 10c is illustrated. The autonomous swarm system 10c is supported by the application of swarm fleet 200, swarm fleet management 110, and swarm protocol 31, and simplifies the industrial environment of production.

[0097] Cluster Agent Configuration: Each cluster agent 210 can specify its role in the cluster agent fleet 200 by defining a cluster agent description. The cluster agent description defines the operational capabilities 211 and behaviors 212 of the cluster agent 210. The configuration of the cluster agent 210 is achieved by exchanging configuration data between the cluster core 100 and the cluster agent 210 using the cluster protocol 31.

[0098] Group Machine Workpiece Configuration: Each group machine workpiece 220 can specify its role in the group machine fleet 200 by defining a group machine workpiece description. Group machine workpiece statements define the execution operation services 221 provided by the group machine workpiece 220. The configuration of the group machine workpiece 220 is achieved through configuration data exchanged between the group machine core 100 and the group machine workpiece 220 using the group machine protocol 31.

[0099] The Cluster Protocol 31 is a communication protocol fully implemented by the Cluster Core 100, Cluster Agent 210, and Cluster Artifact 220 within the Cluster Autonomous System 10c. The configuration parameters of Cluster Protocol 31 can be set by the Cluster Core 100 through a series of configuration UIs and tools. Cluster Protocol 31 supports both local cluster participants and encapsulated cluster participants.

[0100] Local cluster participants include all cluster cores 100, cluster agents 210, and cluster artifacts 220 that fully or partially support cluster protocol 31.

[0101] The encapsulated swarm participants include the swarm core 100, swarm agent 210, and swarm artifact 220, which support a specific communication protocol other than swarm protocol 31. The swarm core 100, swarm agent 210, and swarm artifact 220 need to include a swarm protocol encapsulator to translate their original protocols into swarm protocol 31. The swarm protocol encapsulator can be configured as a software module or a combination of hardware and software.

[0102] Cluster operation depends on the configuration of the cluster core 100, cluster agent 210, and cluster artifact 220. The cluster core 100 can establish task sequencing and task prediction to execute cluster operation tasks. The cluster core 100 manages the cluster operation tasks, while the cluster agent 210 and cluster artifact 220 within the cluster fleet 200 execute these tasks. Cluster operation configuration parameters can be set within the cluster core 100 through a set of configuration UIs and tools.

[0103] The swarm role 130 can be defined by a swarm run executed by the swarm agent 210. A swarm run is defined as a basic sequence of operations of behavior 212. The swarm role 130 specifies a set of capabilities 211 as requirements that the swarm agent 210 must satisfy to perform the swarm run. Capabilities 211 describe the operational capabilities and limitations of a specific swarm participant. The swarm core is also configured to acquire multiple capabilities of each swarm participant, including multiple physical capabilities, multiple operational capabilities, and multiple sensory capabilities. The swarm role 130 can be used as a template for defining tasks. As a result, the actual task to be performed is described by the swarm run defined by the swarm role 130.

[0104] Cluster plan 120 defines batches of tasks based on a task sequence. To achieve this, each cluster plan 120 needs to specify a set of cluster roles 130, execution descriptions, and triggering events. Once a cluster plan 120 is triggered, it will automatically generate a batch of tasks according to the specified cluster roles 130 and task order.

[0105] Subsequently, by meeting the manufacturing process requirements defined by the cluster program 120, the correct configuration is generated to achieve dynamic configuration.

[0106] Figure 5 This is a group-machine autonomous method provided in one embodiment of this application. Figure 5 Each step shown represents one or more steps, methods, or sub-steps in the example method. Furthermore, the order of the steps is illustrative, and steps may be added or removed without departing from the scope of this application.

[0107] S100: The autonomous swarm system defines and configures at least one swarm of locomotives.

[0108] Understandably, in step S100, the autonomous group system 10 defines and configures at least one group of locomotives 200, and configures the group agent 210 and group workpiece 220 within the group of locomotives 200. After the configuration of at least one group of locomotives 200 is completed, the autonomous group system 10 performs a self-test to determine whether the functions of the group agent 210 and group workpiece 220 are normal.

[0109] S200: The group autonomous system defines a group protocol and sets the QoS of the group fleet.

[0110] Understandably, in step S200, the cluster autonomous system 10 defines a cluster protocol 31 and sets QoS 32 for the cluster agent 210 and cluster artifacts 220. The cluster core 100 configures an encapsulator to encapsulate cluster participants. The cluster autonomous system 10 performs a self-test to determine if cluster awareness is implemented.

[0111] S300: The autonomous system for swarm machines defines the roles, capabilities, behaviors, and services of swarm machine participants.

[0112] It is understandable that in step S300, the autonomous system 10 defines the roles 130, capabilities 211, behaviors 212, and services 221 of the cluster core 100, cluster agent 210, and cluster artifact 220.

[0113] S400: All configuration information for the autonomous system of the group.

[0114] It is understandable that in step S400, the group machine autonomous system 10 configures all the configuration information from steps S100 to S300.

[0115] S500: The group machine autonomous system self-checks whether the dynamic configuration of the group machines is complete.

[0116] Understandably, in step S500, the autonomous system 10 performs a self-check to determine whether the dynamic configuration of the group machines is complete.

[0117] S600: The autonomous system configuration of the group of machines is complete.

[0118] Understandably, in step S600, the autonomous system 10 of the group of machines is configured.

[0119] Figure 6 This is a group-machine autonomous method provided in one embodiment of this application. Figure 6 Each step shown represents one or more steps, methods, or sub-steps in the example method. Furthermore, the order of the steps is illustrative, and steps may be added or removed without departing from the scope of this application.

[0120] S1000: Define and configure at least one fleet of motorcycles.

[0121] It is understood that in step S1000, the group machine core 100 defines and configures at least one group of machine fleets 200. The at least one group of machine fleets 200 includes at least one group of machine agents 210. The at least one group of machine fleets 200 also includes at least one group of machine workpieces 220.

[0122] S1010: Configure group participants.

[0123] It is understood that in step S1010, the cluster core 100 configures the cluster participants. The cluster participants include the cluster core 100, the cluster agent 210, and the cluster artifact 220 in the cluster autonomous system 10.

[0124] S1020: Determine if the group participants are ready.

[0125] Understandably, in step S1020, the cluster core 100 determines whether the cluster participants are ready. If the cluster participants are not ready, the process returns to step S1000 to redefine and reconfigure the cluster fleet 200.

[0126] S1030: Defines cluster machine awareness for production operation scenarios.

[0127] It is understandable that in step S1030, the cluster core 100 defines cluster perception in the production execution scenario. The definition of cluster perception is the same as that described in the cluster autonomous system 10, and will not be repeated here.

[0128] S1040: Determine whether group machine perception has been implemented.

[0129] Understandably, in step S1040, the cluster core 100 determines whether cluster sensing has been implemented. If cluster sensing is not ready, the process returns to step S1030 and cluster sensing is redefined.

[0130] S1050: Defines group machine collaboration for production operation scenarios.

[0131] It is understandable that in step S1050, the cluster core 100 defines cluster collaboration in the production execution scenario. The definition of cluster collaboration is the same as that described in the cluster autonomous system 10, and will not be repeated here.

[0132] S1060: Determine whether group machine collaboration is achieved.

[0133] Understandably, in step S1060, the cluster core 100 determines whether cluster collaboration has been achieved. If cluster collaboration is not ready, the process returns to step S1050 and cluster collaboration is redefined.

[0134] S1070: Defines the dynamic configuration process for cluster machines.

[0135] It is understandable that in step S1070, the cluster core 100 defines the dynamic configuration process. The definition method of the cluster dynamic configuration process is the same as that described in the cluster autonomous system 10, and will not be repeated here.

[0136] S1080: Determine whether the dynamic configuration process for the group of machines has been implemented.

[0137] Understandably, in step S1080, the cluster core 100 determines whether the cluster dynamic configuration process has been completed. If the cluster dynamic configuration process is not ready, it returns to step S1070 and redefines the cluster dynamic configuration process.

[0138] S1090: Deployment of the autonomous system for clustered machines is complete.

[0139] Understandably, in step S1090, the swarm autonomous system 10 is deployed. After configuration, the swarm autonomous system 10 is capable of sensing, collaboration, and dynamic configuration.

[0140] Those skilled in the art should recognize that the above embodiments are only used to illustrate this application and are not intended to limit this application. Any appropriate changes and variations made to the above embodiments within the essential spirit and scope of this application fall within the scope of protection claimed in this application.

Claims

1. A swarm autonomous system for industrial applications, the swarm autonomous system comprising a swarm core and at least one swarm vehicle fleet, the at least one swarm vehicle fleet comprising at least one swarm agent, wherein: The cluster core is configured to manage the cluster autonomous system and generate cluster plans and a first configuration of the cluster plans, wherein the first configuration is configured as a set of cluster roles and relationships in production operations; as well as The fleet of aircraft is configured to perform the production operations according to the fleet schedule; The at least one fleet of vehicles also includes at least one fleet of workpieces; The swarm core is further configured to generate a second configuration for the at least one swarm vehicle fleet and swarm participants therein, wherein the swarm participants include swarm agents and swarm artifacts. The cluster core communicates with at least one cluster agent and at least one cluster workpiece via a cluster protocol, wherein the cluster protocol transmits operating data, planning data, monitoring data and configuration data between the cluster core, the at least one cluster agent and the at least one cluster workpiece; The cluster protocol includes a Quality of Service (QoS) policy, wherein the QoS policy is configured to define the network requirements for the runtime data, the planning data, the monitoring data, and the configuration data.

2. The autonomous swarm system according to claim 1, characterized in that, The cluster core is also configured to avoid cluster failures, including participant failures, operational failures, and network failures.

3. The swarm autonomous system according to claim 2 further includes a swarm decision group, wherein, The group decision group is defined as a subgroup of the group of machines, and the group decision group is configured to perform the production operation in adverse execution scenarios or network conditions.

4. The autonomous swarm system according to claim 3, characterized in that, The group decision group also includes a group leader configured to exchange execution information with at least one group member outside the group decision group, wherein the at least one group member includes the group core, the at least one group agent, and the at least one group artifact.

5. The autonomous swarm system according to claim 4, characterized in that, Communication between at least one group member within the group decision group is configured as a distributed topology.

6. The autonomous swarm system as described in claim 1, characterized in that, The cluster planning includes task sorting, task prediction, and task recalculation; The task sorting includes a list of tasks for the production operation, and the task sorting also includes the relationships between tasks; The task prediction includes subsequent tasks ordered according to the task; and The task recalculation is configured to perform task rescheduling and task re-prediction after a fault is detected.

7. The autonomous swarm system according to claim 1, characterized in that, The swarm autonomous system further includes a swarm protocol encapsulator, wherein the swarm protocol encapsulator is connected to the swarm core, the at least one swarm agent, and the at least one swarm artifact, and the swarm protocol encapsulator is configured to convert its original protocol into the swarm protocol.

8. A swarm autonomous system method applied to a swarm autonomous system, the swarm autonomous system comprising a swarm core and at least one swarm vehicle fleet, the at least one swarm vehicle fleet comprising at least one swarm agent, wherein, The method includes: Manage the autonomous cluster system and generate a cluster plan and a first configuration of the cluster plan, wherein the first configuration is configured as a set of cluster roles and relationships in production operations; The fleet of aircraft is configured to perform the production operation according to the fleet plan, and the production operation involves the scenarios of perception, collaboration and dynamic configuration. The at least one fleet of vehicles also includes at least one fleet of workpieces; Generate a second configuration for the at least one swarm vehicle fleet and swarm vehicle participants therein, wherein the swarm vehicle participants include swarm vehicle agents and swarm vehicle artifacts; The system communicates with at least one cluster agent and at least one cluster artifact via a cluster protocol, wherein the cluster protocol is configured to transfer operational data, planning data, monitoring data and configuration data between the cluster core, at least one cluster agent and at least one cluster artifact. The cluster protocol includes a Quality of Service (QoS) policy, wherein the QoS policy is configured to define the network requirements for the runtime data, the planning data, the monitoring data, and the configuration data.

9. The autonomous group method as described in claim 8, characterized in that, The method further includes: Define the cluster machine awareness of the production operation scenario, which is achieved through cluster machine protocol, quality of service, and avoidance of cluster machine failures; Determine whether the group machine perception is implemented; Define the group machine collaboration in the production operation scenario, wherein the group machine collaboration is achieved by defining group machine roles, capabilities, and group machine plans; Determine whether the group machine collaboration is achieved; If the aforementioned cluster collaboration is achieved, then a cluster dynamic configuration process is defined, which is implemented by deploying the configuration of the cluster solution; Determine whether the dynamic configuration process for the cluster machines has been implemented; If the dynamic configuration process of the cluster machines is completed, the deployment of the autonomous cluster machine system is finished.

10. The swarm autonomous method as described in claim 9, characterized in that, The cluster sensing is also implemented through a cluster protocol encapsulator, wherein the cluster protocol encapsulator is connected to the cluster core, the at least one cluster agent, or the at least one cluster artifact, and the cluster protocol encapsulator is configured to translate its original protocol into the cluster protocol.

11. The swarm autonomous method as described in claim 8, characterized in that, The method further includes: To avoid cluster machine failures, wherein the cluster machine failures include participant failures, operational failures, and network failures.

12. The swarm autonomous method as described in claim 9, characterized in that, The method further includes: A group of machine decision groups is set up, wherein the group of machine decision groups is defined as a subgroup of the group of machine fleets, and the group of machine decision groups is configured to perform the production operation in adverse execution scenarios or network conditions.

13. The swarm autonomous method as described in claim 12, characterized in that, The method further includes: A group of leaders is set up within the group machine resolution group, wherein the group leaders are configured to exchange execution information with at least one group machine member outside the group machine resolution group, wherein the at least one group machine member includes the group machine core, the at least one group machine agent, and the at least one group machine artifact.

14. The swarm autonomous method as described in claim 13, characterized in that, The method further includes: The communication between at least one group member within the group decision group is configured as a distributed topology.

15. The autonomous group method as described in claim 8, characterized in that, The method further includes: Generate a task sort, wherein the task sort includes a list of tasks for the production operation, and the task sort also includes the relationships between tasks; Generate a task prediction, wherein the task prediction includes subsequent tasks ordered according to the task; and A task recalculation is generated, wherein the task recalculation is configured to perform task rescheduling and task re-prediction after a fault is detected.

Images