Multilevel production processes are integrated utilizing as input a relatively lower production level. Activities at the lower production level producing an end product and physical parameters that influence these activities are identified, the identified physical parameters are measured with sensors, and a quota fulfillment probability index for an activity is determined using the measured physical parameters. The quota fulfillment probability index is supplied to a production entity operating at a consecutive, relatively higher production level than the activities at the relatively lower production level.

A KUBERNETES installation processes a script and invokes a scheduling agent in response to encountering an instruction to create a pod. The scheduling agent is an agent of an orchestrator and performs tasks such as identifying a selected node, creating multiple interface objects with multiple IP addresses, and creating storage volumes in coordination with the orchestrator. Upon creation, the pod may call a CNI that is an agent of the orchestrator in order to configure the pod to use the multiple interface objects. The pod may call a CSI that is an agent of the orchestrator in order to bind a storage volume to the pod. The scheduling agent may coordinate with the orchestrator to implement affinity and anti-affinity rules for placement of pods and storage volumes. The script may also be transformed by the orchestrator in order to insert instructions implementing affinity and anti-affinity rules.

A peer-to-peer interaction management system for optimizing flexible manufacturing comprising a plurality of peers and comprises rules for defining the data interaction, operational interaction, environmental interaction and safety interaction. The plurality of peers comprising a robot control server and a plurality of autonomous mobile robots. One peer can exchange data with another peer, the data can comprise planning data, operational data, monitor data, and safety data.

A KUBERNETES installation processes a script and invokes a scheduling agent in response to encountering an instruction to create a pod. The scheduling agent is an agent of an orchestrator and performs tasks such as identifying a selected node, creating multiple interface objects with multiple IP addresses, and creating storage volumes in coordination with the orchestrator. Upon creation, the pod may call a CNI that is an agent of the orchestrator in order to configure the pod to use the multiple interface objects. The pod may call a CSI that is an agent of the orchestrator in order to bind a storage volume to the pod. The scheduling agent may coordinate with the orchestrator to implement affinity and anti-affinity rules for placement of pods and storage volumes. The script may also be transformed by the orchestrator in order to insert instructions implementing affinity and ant-affinity rules.

The present invention relates to the field of control engineering, in particular to a distributed control method for consensus of an agricultural multi-agent system based on sampled data, comprising the following steps: for a first-order multi-agent system with fixed directed topology, designing a distributed control protocol based on sampled information in a time delay state; obtaining a dynamic model of the multi-agent system with time delays based on sampled information, and transforming a consensus problem of multiple agents into a stability problem by means of tree transformation; determining constraint conditions on a time delay and a sampling period that the multi-agent system achieves stability, that is, sufficient and necessary conditions that the agents in the multi-agent system achieve average state consensus; and realizing average consensus of the multi-agent system according to the sufficient and necessary conditions.

Systems, methods, devices, and other techniques for planning and re-planning robot motions. The techniques can include obtaining a schedule that defines an execution order for a plurality of plans, each plan defining a sequence of tasks; providing instructions to the robotic system to execute plans from the plurality of plans according to the schedule; obtaining measurements for one or more parameters that represent a state of the robotic system or its environment that results from execution of at least one plan from the plurality of plans; determining, based on the measurements, that a particular plan from the plurality of plans, which has not completed execution, is to be revised; generating, using the measurements, a revised version of the particular plan; and adjusting the schedule so as to resolve a conflict between the revised version of the particular plan and at least one other plan in the plurality of plans.

An automated shuttle sorter is disclosed that includes a carriage that is movable from a load position at which the carriage may be loaded, and at least two destination locations into which any contents of the carriage may be provided from the carriage.

A battery reservation device (10) includes an input acceptance component (11), a battery number acquisition component (12), and a rental number and capacity calculator (15). The input acceptance component (11) inputs from the user information related to the total power amount of the battery packs (1) that is desired to be rented. The battery number acquisition component (12) acquires information related to the number of battery packs (1) that are installed in a vehicle (20). The rental number and capacity calculator (15) calculates the number and capacity of the battery packs (1) that are rentable at each battery station (30) on the basis of information related to the number of battery packs (1) acquired by the battery number acquisition component (12) and the total power amount of the battery packs (1) inputted to the input acceptance component (11).

According to various aspects, controller for an automated machine may include: a processor configured to: compare information about a function of the automated machine with information of a set of tasks available to a plurality of automated machines; negotiate, with the other automated machines of the plurality of automated machines and based on a result of the comparison, which task of the set of tasks is allocated to the automated machine.

The apparatus for distributed collaborative resource allocation receives order information and job start information for each process from a factory agent, calculates a slack time of a job used as an evaluation indicator for an order through the order information and job start information for each process, determines participation in a job on the order using the evaluation indicator of each machine agent, sets a machine agent having the highest evaluation indicator among machine agents for each process representing the participation as a negotiating agent for a corresponding process, and proceeds with negotiation for production quantity with the remaining machine agents representing the participation in the corresponding process.