The user experience in industrial human-robot interaction: A comparative analysis of Unimodal and Multimodal interfaces for disassembly tasks

• Evaluates how unimodal and multimodal interfaces impact operators’ cognitive and emotional responses during disassembly tasks, using EEG data for objective measurement along with perceptual and performance metrics. • Demonstrates that multimodal interfaces not only reduce cognitive workload and memorization needs but also enhance operator performance and well-being, making them more accessible and effective for satisfying human-robot collaboration. This aligns with Industry 5.0′s focus on personalizing technology to human needs. • Advocates for the integration of comprehensive physiological and perceptual measurements to optimize interface design, ensuring technology adapts to diverse user needs and enhances overall user experience in industrial applications. In the Industry 5.0 context, ensuring effective Human-Robot Interaction (HRI) is key to supporting human involvement in production processes. Interfaces are the foundation of this collaboration and serve as vital communication channels which bridge the gap between users and robotic systems. This study compares unimodal and multimodal interfaces and their impact on user experience (UX) in an HRI context. Unimodal interfaces, while simplifying implementation, may restrict the richness of communication, while multimodal interfaces provide detailed and flexible interaction, enhancing the conveyance of complex information. However, designing effective multimodal interfaces presents challenges due to their inherent complexity in managing multiple modalities. This paper presents an HRI disassembly case study comparing the impact of these interfaces on the UX. A methodological approach was used to monitor operator performance, physiological responses, and perceptual responses. An electroencephalogram was employed to objectively record the operators’ emotional responses of operators without interrupting or hindering the process. Twenty participants (10 men and 10 women) were involved in the study. The results indicate that levels of memorization and mental workload are lower when using the multimodal interface, a finding consistent across men and women. These findings suggest that the multimodal interface is an appropriate choice, not only for reducing memorization and mental workload levels, but also for its inclusive approach. This aligns with the objectives of Industry 5.0, promoting the development of technology that meets diverse user preferences and abilities, thereby ensuring greater accessibility and a more user-centric technological landscape.

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Publication Details

Journal
Robotics and Computer-Integrated Manufacturing
Published
2025-05-02
DOI
https://doi.org/10.1016/j.rcim.2025.103045
Citations
5
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
12.19
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article

The user experience in industrial human-robot interaction: A comparative analysis of Unimodal and Multimodal interfaces for disassembly tasks

Ganix Lasa, Maitane Mazmela, Amaia Etxabe, Ainhoa Apraiz et al.
5 citations
Robotics and Computer-Integrated Manufacturing
Human-Automation Interaction and Safety
12.19
article

The user experience in industrial human-robot interaction: A comparative analysis of Unimodal and Multimodal interfaces for disassembly tasks

Ganix Lasa, Maitane Mazmela, Amaia Etxabe, Ainhoa Apraiz, Íñigo Elguea-Aguinaco, Nestor Arana-Arexolaleiba, Oscar Escallada, Nagore Osa
article en
5 citations

Abstract

• Evaluates how unimodal and multimodal interfaces impact operators’ cognitive and emotional responses during disassembly tasks, using EEG data for objective measurement along with perceptual and performance metrics. • Demonstrates that multimodal interfaces not only reduce cognitive workload and memorization needs but also enhance operator performance and well-being, making them more accessible and effective for satisfying human-robot collaboration. This aligns with Industry 5.0′s focus on personalizing technology to human needs. • Advocates for the integration of comprehensive physiological and perceptual measurements to optimize interface design, ensuring technology adapts to diverse user needs and enhances overall user experience in industrial applications. In the Industry 5.0 context, ensuring effective Human-Robot Interaction (HRI) is key to supporting human involvement in production processes. Interfaces are the foundation of this collaboration and serve as vital communication channels which bridge the gap between users and robotic systems. This study compares unimodal and multimodal interfaces and their impact on user experience (UX) in an HRI context. Unimodal interfaces, while simplifying implementation, may restrict the richness of communication, while multimodal interfaces provide detailed and flexible interaction, enhancing the conveyance of complex information. However, designing effective multimodal interfaces presents challenges due to their inherent complexity in managing multiple modalities. This paper presents an HRI disassembly case study comparing the impact of these interfaces on the UX. A methodological approach was used to monitor operator performance, physiological responses, and perceptual responses. An electroencephalogram was employed to objectively record the operators’ emotional responses of operators without interrupting or hindering the process. Twenty participants (10 men and 10 women) were involved in the study. The results indicate that levels of memorization and mental workload are lower when using the multimodal interface, a finding consistent across men and women. These findings suggest that the multimodal interface is an appropriate choice, not only for reducing memorization and mental workload levels, but also for its inclusive approach. This aligns with the objectives of Industry 5.0, promoting the development of technology that meets diverse user preferences and abilities, thereby ensuring greater accessibility and a more user-centric technological landscape.

Robotics and Computer-Integrated ManufacturingVol. 95
Mondragon Unibertsitatea (ES)
Decent work and economic growth
Openalex Percentile: Top 2%
Human-Automation Interaction and Safety
12.19
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