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Test robot to maintain safe distance from the operator in a Hand-Guiding task

The purpose of this protocol is to validate the safety skill “maintain safe distance” for hand-guided robots, eventually equipped with tracking technologies and collision avoidance controllers, where a limb of a subject has a free connection point with the robot and the robot can move that point within a 3D volume while preventing collision with the operator’s limbs. The minimum distance between robot internal links and subject limbs during operation must be ensured. This is validated using an instrumented limb attached to the robot end effector and a sensor system mounted on the robot.

COVR ROB-MSD-4

Test 3D Safety Sensors in Speed and Separation Monitoring Cobot Applications

The purpose of this protocol is to validate suitability of 3D sensors, particularly LiDAR scanners, for improving the skill “Maintain Safe Distance” in advanced Speed and Separation Monitoring (SSM) cobot applications . Besides the sensors’ technical characteristics, the data processing, and decision-making abilities of an associated intelligent control system (ICS) are the subject of validation. Such ICS periodically acquires of a COBOT and an operator, eventually predicts their positions in a the positions near future, and adjusts the COBOT’s velocity to keep their mutual distance above the accordingly updated protective separation distance (PSD). The validation test checks with assistance of a high-speed high-resolution camera whether the ICS implements the SSM functionality successfully to prevent collisions between the robot and the operator in a systematically chosen repertoire of collaborative situations identified as potentially hazardous in the risk assessment. This protocol was developed in the COVR funded FSTP project “CobotSense” by FOKUS TECH, the Maribor, and FANUC ADRIA, and was published as a deliverable for that project.

COVR ROB-MSD-3

Correct evaluation of collaborative robot safety (Focus on IFA works No. 0419)

This document gives guidance for measuring forces and pressures in human-robot collision. It summarizes the findings of a research projects and supports the interpretation of results from such measurements.

DGUV 617.0-IFA:638.22

Engineering data exchange format for use in industrial automation systems engineering - Automation Markup Language - Part 1: Architecture and general requirements

IEC 62714-1:2018 is a solution for data exchange focusing on the domain of automation engineering. The data exchange format defined in the IEC 62714 series (Automation Markup Language, AML) is an XML schema based data format and has been developed in order to support the data exchange in a heterogeneous engineering tools landscape. The goal of AML is to interconnect engineering tools in their different disciplines, e.g. mechanical plant engineering, electrical design, process engineering, process control engineering, HMI development, PLC programming, robot programming, etc. This second edition cancels and replaces the first edition published in 2014. This edition constitutes a technical revision. This edition includes the following significant technical changes with respect to the previous edition:a) use of CAEX 3.0 according to IEC 62424:2016b) improved modelling of references to documents outside of the scope of the present standard,c) modelling of references between CAEX attributes and items in external documents,d) revised role libraries,e) modified Port concept,f) modelling of multilingual expressions,g) modelling of structured attribute lists or array,h) a new AML container format,i) a new standard AML attribute library

IEC 62714-1:2018

Core Network and Interoperability Testing (INT/WG AFI); Federated GANA Knowledge Planes (KPs) for Multi-Domain Autonomic Management & Control (AMC) of Slices in the NGMN® 5G End-to-End Architecture Framework

As part of the growing area of Autonomic/Autonomous Networks (ANs), the document covers the subject of Federated GANA Knowledge Planes (KPs) Platforms for E2E Multi-Domain Federated Autonomic Management and Control (AMC) of 5G Network Slices in NGMN® E2E 5G Architecture

ETSI TR 103 747

ETSI GANA as Multi-Layer Artificial Intelligence (AI) Framework for Implementing AI Models for Autonomic Management & Control (AMC) of Networks and Services; and Intent-Based Networking (IBN) via GANA Knowledge Planes (KPs)

Provides insights on ETSI GANA Knowledge Planes (KPs) Driven Networking in Autonomic/Autonomous Networking (ANs) for Networks that exhibit features such as self-* operations such as self-adaptation, self-optimization, self-monitoring, self-protection and self-defense objectives for the network and services; Establishes relationships between Autonomics, Cognition and Autonomous Network Behaviour; Standardization in this area of ANs.

ETSI 5G PoC White Paper No. 4

IEEE INGR (International Network Generations Roadmap)/Future Networks, Standardization Building Blocks (SBB) Roadmap Chapter

Discusses Standards Roadmaps for Future Networks, including 5G/6G, as well as in the area of Autonomic/Autonomous Networking (ANs) Standards. The Emerging Industry Requirement for Standardization of a Blueprint for Common Operational Principles for Autonomic/Autonomous Networks (COPAAN) is presented in relation to the Autonomic/Autonomous Networking (ANs) paradigm. The connection of COPAAN and Robotics is illustrated.

IEEE NGR (International Network Generations Roadmap) 2022 EDITION

IEEE INGR (International Network Generations Roadmap)/Future Networks, Systems Optimization Roadmap Chapter

The document describes Gaps in Standards for Autonomic/Autonomous Networking (ANs), including Self-Organizing Systems and Networks. The Emerging Industry Requirement for Standardization of a Blueprint for Common Operational Principles for Autonomic/Autonomous Networks (COPAAN) is presented in more detail in relation to the Autonomic/Autonomous Networking (ANs) paradigm. The Model of Interfaces of an AN that call for COPAAN Standard Development is presented. The connection of COPAAN and Robotics is illustrated. Systems Optimization, Traffic Variance, Control Variance, Service Variance, Confluence, Dependency, Complex Systems, Self-Organizing Networks, Self-X, Autonomics, Autonomic Management & Control (AMC), Emergence

IEEE NGR (International Network Generations Roadmap) 2022 EDITION

ITU-T Focus Group on “Autonomous Networks” (FG-AN)

Provides information on Study to identify and close gaps in Standards for Autonomous Networks (ANs) to complement Standards on ANs developed elsewhere such as the ETSI GANA related Standards

Terms of Reference