Simulation-based testing for human-robot collaboration

Simulation-based testing, Human-robot collaboration, Constraint-based modelling, Knowledge modelling, Test oracles, Artificial intelligence.

Method Purpose Short description of the method's purpose and main benefits

Method description A detailed description of the method

The evolution towards the Industry 4.0 paradigm aims to increase flexibility and robustness by maintaining the level of productivity. To meet these requirements, collaboration between humans and robots is considered a basic framework within the future intelligent manufacturing cells. However, this interaction between humans and robots is a complex process that raises challenges around compatibility and operational safety. Test-based simulation for human-robot collaboration provides the opportunity to evaluate the feasibility and performance of the system, particularly the layout or workplace planning, production reliability and, especially, the safety and efficiency of human-robot collaboration.

Validating the safety of an HRI (Human Robot Interaction) application is not a trivial task. The simulation is key to the validation in this type of systems [SBT1, SBT5, SBT6]. Through simulation, a high percentage of the safety requirements can be validated without putting any human at risk. In the domain of HRI applications, the relevant value space of input variables in tests and simulations can approach infinity (ill-defined domains), even more when dealing with people with different disabilities. In this context, specifying the oracles and assertions of the different tests remains a complex task.

Previous works [SBT2, SBT3, SBT4] have utilized onstraint-based modelling techniques to interpret and diagnose procedural task carried out by users, including humans with disabilities. The objective of this work is to integrate a framework that will act as an oracle in a simulation-based testing environment. This simulation will provide real time diagnosis for the interaction between disabled humans and robots in a manufacturing and disassembly domain.

Method Strengths A listof the strengths of the method

In simulation-based testing, verification activities can be done for different robots without changing other models or tools. Also, system-testing can be done without producing any physical item and adding risk to environment.
Constraint-based modelling of oracles can provide powerful asserts in complex simulation testing.

Method Limitations The limitations of the method

The generation of Constraint-based knowledge model is a complex and time-consuming task.
Simulation tools that used constraint-based modelling for assertion can require much computational power and limits real-time applications.

Method References Bibliography references to papers about the method.

[SBT1] Koenig, N., & Howard, A. (2004, September). Design and use paradigms for gazebo, an open-source multi-robot simulator. In 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(IEEE Cat. No. 04CH37566) (Vol. 3, pp. 2149-2154). IEEE.
[SBT2] Aguirre, A., Lozano-Rodero, A., Matey, L. M., Villamañe, M., & Ferrero, B. (2014). A novel approach to diagnosing motor skills. IEEE Transactions on Learning Technologies, 7(4), 304-318.
[SBT3] Aguirre, A., Lozano-Rodero, A., Villamañe, M., Ferrero, B., & Matey, L. M. (2012).OLYMPUS: An Intelligent Interactive Learning Platform for Procedural Tasks. In GRAPP/IVAPP (pp. 543-550).
[SBT4] Ostiategui, F., Amundarain, A., Lozano, A., & Matey, L. (2010). Gardening Work Simulation Tool in Virtual Reality for Disabled People Tutorial. Proceedings of Integrated Design and Manufacturing-Virtual Concept (IDMME’10).
[SBT5] Webster, M., Western, D., Araiza-Illan, D., Dixon, C., Eder, K., Fisher, M., & Pipe, A. G.(2020). A corroborative approach to verification and validation of human–robot teams. The International Journal of Robotics Research, 39(1), 73-99.
[SBT6] Takaya, K., Asai, T., Kroumov, V., & Smarandache, F. (2016, October). Simulation environment for mobile robots testing using ROS and Gazebo. In 2016 20th International Conference on System Theory, Control and Computing (ICSTCC) (pp. 96-101). IEEE.

Method Dimensions

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)

Relations

Related Methods A method could be related to other methods.

Tools A method can use zero or more tools.

Part Method A method (when it is a combination: Combination of method artefact that is a specialization of a V&V Method) could be composed of a set of V&V Methods.

Test Case or Verification and Validation activity Test Case or V&V activity performed in a Use Case. We will link to the method to the test cases where the method is used.

Standards A method can be linked with standards.

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