Evaluation Scenario Requirements

Evaluation Scenario Requirements List

• UC4_R_20 Information about robot input and output signals
• UC4_R_3 Direct line of sight
• UC4_R_4 Human in working space
• UC4_R_5 Availability of robot-specific look-up tables for speed and distances
• UC4_R_6 Minimal distance calculation
• UC4_R_7 Robot joint angles data available
• UC4_R_8 Robot tool center point coordinates available
• UC4_R_9 Robot tool center point speed available
• UC4_R_10 Air pressure activated
• UC4_R_11 Availability of part at conveyor belt
• UC4_R_12 Available proximity sensor data
• UC4_R_13 Display of the current/actual line in robot program
• UC4_R_14 Program lines information
• UC4_R_15 Information about the robot tool state
• UC4_R_16 Coordinates of the robot tool center point (TCP)
• UC4_R_21 Access to HTTP-Client (REST)
• UC4_R_22 Access to HTTP-Server (REST)
• UC4_R_23 Access to IoT-Gateway
• UC4_R_24 Hashcodes / checksums for manipulation source identification

V&V Methods

V&V Methods List of the methods used in this evaluation scenario

• Model-based fault injection for safety analysis Method for automatic injection of faults into a formal model
• Simulation-Based Testing for Human-Robot Collaboration Simulation-based testing, Human-robot collaboration, Constraint-based modelling, Knowledge modelling, Test oracles, Artificial intelligence.
• Virtual Architecture Development and Simulated Evaluation of Software Concepts The approach with its corresponding simulation and virtual validation framework FERAL (Framework for fast Evaluation on Requirements and Architecture Level) is a solution for virtual architecture development and simulated evaluation of software concepts. FERAL allows the design of virtual prototypes, which replace real prototypes by means of simulation and evaluate the impact of new architecture concepts in a cost-efficient manner. The solution enables simulation-based validation and the systematic assessment of design decisions at an early stage by coupling simulation models and simulators, existing code, and virtual hardware platforms.
• Model-based testing Automatically derive test cases from behavioural models of a system/component to check for correct behaviour.
• Model-Based Safety Analysis
• Model-based threat analysis A model of the system/component including cybersecurity attributes is analysed to find weaknesses and vulnerabilities based on a threat database.
• Failure Detection and Diagnosis (FDD) in Robotic Systems FDD is a data-driven process monitoring and testing method for minimising downtimes, increase the safety of operations, and to reduce manufacturing costs. FDD comprises different approaches that can be distinguished into data-based, model-based, and knowledge-based approaches.

VALU3S Framework

Evaluation Environment Type Type of environment where the method is applied. It can be more than one type of environment.(Dimension 1)

Evaluation Type Type of evaluation performed with that method. If a method is hybrid, more than one type can be selected.(Dimension 2)

Type of Component Under Evaluation Type of components that can be evaluated with that method. It can be more than one type.(Dimension 3)

Evaluation Stage The evaluation stage where the method is used.(Dimension 5)

Purpose of the Component Under Evaluation The type of purpose that can be evaluated by a method. It can be more than one type.(Dimension 6)

Type of Requirement Under Evaluation The type of requirements that a method is able to evaluate. It can be more than one type.(Dimension 7)

Evaluation Performance Indicator The type of evaluation criteria or KPI that a method is able to improve. It can be more than one type.(Dimension 8)

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