The student Ainhoa Apraiz Iriarte obtained an EXCELLENT CUM LAUDE grade

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The student Ainhoa Apraiz Iriarte obtained an EXCELLENT CUM LAUDE grade

THESIS

The student Ainhoa Apraiz Iriarte obtained an EXCELLENT CUM LAUDE grade

2023·12·18

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  • Thesis title: Nuevo modelo de evaluación de la Interacción Persona-Robot en entornos industriales: ITPX-ROBOTS

Court:

  • Presidency: José Antonio Diego Más (Universitat Politècnica de València)
  • Vocal: Aiur Retegi Uria (Universidad de Deusto)
  • Vocal: Iñigo Bediaga Escudero (Ideko S. Coop)
  • Vocal: Carlos Calleja Elcoro (Ikerlan S. Coop)
  • Secretary: Arantxa Glez. de Heredia López de Sabando (Mondragon Unibertsitatea)

Abstract:

The industry 5.0 has as its main pillar the well-being of people, thus redefining the role of individuals and transforming current job positions into formats that are still unknown. This research focuses on one of the most relevant challenges for Industry 5.0: Human-Robot Interaction (HRI).

With the aim of ensuring the successful acceptance of robots by people, this research introduces the Individual Task Performance Experience – Robots (ITPX-ROBOTS) model as a proposal to assess the suitability of robotic systems in relation to individuals and to evaluate task achievement in terms of performance, physiology, and perception.

In this context, this doctoral thesis introduces the conceptual framework of Human-Robot Interaction Experience (HRIX), which illustrates how the alignment between the characteristics of the entities involved in the interaction (person, robot, and context) impacts the User Experience (UX) and its components. In the HRI environment, these components include utility, ease of use, comfort, learnability, and controllability. All of these factors have consequences for human-related factors such as attitude and intention to use, trust, perceived safety, and satisfaction.

Furthermore, the model is based on the Human-Robot-Context taxonomy (HUBOXT), which identifies (i) the characteristics of the person, (ii) the characteristics of the robot, and (iii) the characteristics of the context that influence the acceptance of HRI.

Considering the conceptual framework and the taxonomy, the ITPX-ROBOTS model is proposed, which is divided into three phases, following a holistic approach to UX evaluations, in line with the ITPX model (Mazmela, 2020). These three stages encompass: (i) the pre-interaction evaluation, which focuses on expert evaluation using heuristics; (ii) the evaluation during the interaction, which involves collecting performance indicators and physiological parameters during the execution of tasks with the robot; and (iii) the post-interaction evaluation, which focuses on obtaining user perceptions about the interaction they have experienced with the robot.

To execute the pre-interaction phase, HEUROBOX has been developed, a new set of heuristics that groups design guidelines into a logical list of heuristics for evaluating the interaction between people and robots in industrial environments. To complement the post-interaction phase, the HUROX questionnaire has been developed, designed to evaluate the UX in interactions with robots in industrial environments.

The experimental phase of the model has been carried out through two case studies, one related to an assembly task and the other to a disassembly task. The results reveal that the ITPX-ROBOTS model helps diagnose the success of HRI, providing a procedure that facilitates the analysis of the impact of robots on task accomplishment and user perception. Consequently, the thesis presents a model to gain a deeper understanding of the integration of robots, which will enable the optimization of industrial processes, improve quality, and increase productivity effectively.

Some of the significant contributions of this study include:

  • A new model for evaluating Human-Robot Interaction in industrial environments, named ITPX-ROBOTS.
  • A new list of heuristic evaluation criteria for Human-Robot Interaction in industrial environments, named HEUROBOX.
  • A new questionnaire for assessing user perceptions in Human-Robot Interaction in industrial environments, named HUROX.