A method and apparatus for controlling and coordinating a multi-component system. Each component in the system contains a computing device. Each computing device is controlled by software running on the computing device. A first portion of the software resident on each computing device is used to control operations needed to coordinate the activities of all the components in the system. This first portion is known as a coordinating process. A second portion of the software resident on each computing device is used to control local processes (local activities) specific to that component. Each component in the system is capable of hosting and running the coordinating process. The coordinating process continually cycles from component to component while it is running. The continuous cycling of the coordinating process presents the programmer with a virtual machine in which there is a single coordinating process operating with a global view although, in fact, the data and computation remain distributed across every component in the system.

A synchronization primitive provides robots with locks, monitors, semaphores, or other mechanisms for reserving temporary access to a shared limited set of resources required by the robots in performing different tasks. Through non-conflicting establishment of the synchronization primitives across the set of resources, robots can prioritize the order with which assigned tasks are completed and minimize wait times for resources needed to complete each of the assigned tasks, thereby maximizing the number of tasks simultaneously executed by the robots and optimizing task completion. The synchronization primitives and resulting resource allocation can be implemented with a centralized coordinator or with peer-to-peer robotic messaging, whereby private keys and blockchains secure the precedence and establishment of synchronization primitives by different robots. Moreover, synchronization primitives can be established with queues to further optimize the immediate and future allocation of resources to different robots.

Approaches presented herein enable maneuvering collaborative robots to rescue persons in a hydrological disaster. A plurality of robots are dispersed in a body of water to spread out and seek victims using cooperative foraging techniques within resource constraints. A location of victims located by a robot using sensing techniques is communicated to other robots. A situational assessment is performed using victim location information to determine a number of robots to deploy to the location. The deployed robots are directed to perform coordinated maneuvers to create a connected floatation unit to support floatation of victims for rescue.

Techniques are provided for discovery and monitoring of an environment using a plurality of robots. A plurality of robots navigate an environment by determining a navigation buffer for each of the robots; and allowing each of the robots to navigate within the environment while maintaining a substantially minimum distance from other robots, wherein the substantially minimum distance corresponds to the navigation buffer, and wherein a size of each of the navigation buffers is reduced over time based on a percentage of the environment that remains to be navigated. The robots can also navigate an environment by obtaining a discretization of the environment to a plurality of discrete regions; and determining a next unvisited discrete region for one of the plurality of robots to explore in the exemplary environment using a breadth-first search. The plurality of discrete regions can be, for example, a plurality of real or virtual tiles.

Techniques are provided for discovery and monitoring of an environment using a plurality of robots. A plurality of robots navigate an environment by determining a navigation buffer for each of the robots; and allowing each of the robots to navigate within the environment while maintaining a substantially minimum distance from other robots, wherein the substantially minimum distance corresponds to the navigation buffer, and wherein a size of each of the navigation buffers is reduced over time based on a percentage of the environment that remains to be navigated. The robots can also navigate an environment by obtaining a discretization of the environment to a plurality of discrete regions; and determining a next unvisited discrete region for one of the plurality of robots to explore in the exemplary environment using a breadth-first search. The plurality of discrete regions can be, for example, a plurality of real or virtual tiles.

A system for estimating a pose of a robot includes a particle filter to track the pose of the robot using particles that defining a probability of pose of the robot and a particle tuner to update the particles of the robot based on particles of neighboring robot. Upon receiving data indicative of relative pose between a pose of the robot and a pose of a neighboring robot, and particles of the neighboring robot, the particle tuner pairs an arbitrarily sampled particle of the robot with an arbitrarily sampled particle of the neighboring robot, determines a weight of the paired particles in reverse proportion to an error between a relative pose defined by the paired particles and the relative pose between the robot and the neighboring robot, and updates the particles of the robot in accordance to the weights of corresponding paired particles.

A control device for a production module that has a settings management module for detecting restrictions for operating settings of the production module and for producing corresponding restriction data records is provided. A data memory is provided for the purpose of storing a local restriction table containing a multiplicity of restriction data records. A balancing module is used to iteratively read in first restriction data records in a corresponding restriction table of a first adjacent production module, to iteratively build the local restriction table on the basis of the first restriction data records which have been read in and to iteratively forward second restriction data records in the local restriction table to a second adjacent production module. A control module is also provided for the purpose of setting an operating setting according to a restriction data record which identifies this operating setting.

Described in detail herein is an automated fulfillment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Detection of a breakdown sign in a first manufacturing machine forming a production system, prediction of a stop time when operation of the first manufacturing machine stops due to the breakdown, and specification of a maintenance time to return the first manufacturing machine to a normal state when the first manufacturing machine stops operating due to the breakdown. Achievement of a first total productivity planned by the planning unit when the sign of the breakdown is detected during the operation of the first and second manufacturing machines and the stop time of the first manufacturing machine is earlier than the maintenance time, at least the amount of operation of the first manufacturing machine is controlled to be equal to or greater than an amount of operation before the sign of the breakdown is detected, and a second total productivity higher than the first total productivity is set as a total productivity to the stop time.

Robotic applications are important in both indoor and outdoor environments. Establishing reliable end-to-end communication among robots in such environments are inevitable. Many real-time challenges in robotic communications are mainly due to the dynamic movement of robots, battery constraints, absence of Global Position System (GPS), etc. Systems and methods of the present disclosure provide assisted link prediction (ALP) protocol for communication between robots that resolves real-time challenges link ambiguity, prediction accuracy, improving Packet Reception Ratio (PRR) and reducing energy consumption in-terms of lesser retransmissions by computing link matrix between robots and determining status of a Collaborative Robotic based Link Prediction (CRLP) link prediction based on a comparison of link matrix value with a predefined covariance link matrix threshold. Based on determined status, robots either transmit or receive packet, and the predefined covariance link matrix threshold is dynamically updated. If the link to be predicted is unavailable, the system resolves ambiguity thereby enabling communication between robots.