Accenture Global Solutions Limited

Nicholas Akiona

Carl Matthew Dukatz

Teresa Sheausan Tung

Michael Kuniavsky

Andrew Nam

Michael Nai-An Chen

Matthew Lee Austin

Oyinlola Oladiran

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support cross-server containerized application allocation, multi-tenant namespace management, and data layer deployment in an edge environment. To illustrate, containers associated with an application are deployed to edge servers based on a geographic characteristic of the edge server with respect to an edge device receiving services from the application. A common data layer is provided across the edge environment to manage communications between the different containers, and between the application and other applications of the edge environment. Managing the communication is based on namespaces and/or a modality (e.g., private or public) associated with the application. Authentication configuration of the application is used to determine edge resource access for the containers of the application. A common orchestration layer is provided across the edge environment to manage scaling and configuration updates of the application.

Scalable, robust, and secure multi-tenant edge architecture for mission-critical applications

This document describes a simulation system that simulates robots and other actors performing tasks in an area. In one aspect, a method includes obtaining a graph representing a physical area. The graph includes area nodes that represent regions of the area that are traversed by a set of actors that perform tasks in the area and terminal nodes that represent regions of the facility where the actors perform the tasks. A set of agents that each include a model corresponding to an actor is identified. At least a portion of the agents includes models for robots that perform tasks in the area. The model of an agent represents durations of time for traversing area nodes and performing tasks are terminal nodes during simulations. A sequence of tasks being performed in the area is simulated using the graph and the set of agents.

Enhanced robot fleet navigation and control

This document describes a generative design platform that uses style to generate product designs. In one aspect, a method includes receiving, from a client computing device of a user, data identifying a set of design parameters including a product template for a product and one or more style grammars for the product. Each style grammar includes a set of stylistic parameters that define aesthetic characteristics of a group of related products. One or more physical constraints on a design of the product are obtained. A set of candidate product designs for the product are generated based on the product template, each style grammar, and the one or more physical constraints. A set of scores are generated for each candidate product design based on an evaluation of the candidate product designs. A subset of the candidate product designs are selected based on the scores.

Generative design using style grammars

Implementations directed to providing a computer-implemented system for performing an action with a robot comprising receiving command information indicating a command related to performance of an action with a robot, identifying state information for a plurality of active routines that are actively running for the robot, the state information indicating a state for each of the active routines, determining contextual information for the command based on the accessed state information for the plurality of active routines, selecting one of the active routines as a handling routine to service the command based on the contextual information, determining an output module of the robot to perform the action based on the state of the handling routine and the contextual information, and executing one or more instructions to perform the action with the output module.

Robot orchestration architecture

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating multiple distinct test plans using a computing system. The system merges the each of the test plans to produce a first test plan and obtains performance data about automated execution of the first test plan by a robotics system. The system generates learned inferences for determining predictions about execution of the first test plan based on analysis of the performance data and adjusts the first test plan based on the learned inferences. The system generates a second test plan for execution by the computing system based on adjustments to the first test plan and performs the second test plan to test multiple devices using the robotics system.

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San Jose, CA, United States of America

Nicholas Akiona