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A comparison of visual and auditory EEG interfaces for robot multi-stage task control.

Kai Arulkumaran1, Marina Di Vincenzo1, Rousslan Fernand Julien Dossa1

  • 1Araya Inc., Tokyo, Japan.

Frontiers in Robotics and AI
|May 24, 2024
PubMed
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Assistive robots offer shared autonomy for individuals with physical impairments. This study found that users performed and preferred different brain-computer interface modalities (auditory vs. visual stimuli) for robot control, emphasizing personalized human-robot interaction.

Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Neuroscience

Background:

  • Shared autonomy in assistive robotics enables individuals with physical impairments to control robots for task completion.
  • Non-invasive brain-computer interfaces (BCIs), particularly electroencephalography (EEG)-based systems, are common for shared autonomy.
  • Selecting targets (objects or locations) presents a challenge due to the multitude of choices offered by capable robots.

Purpose of the Study:

  • To compare the efficacy and user preference of auditory versus visual stimuli within an oddball paradigm for BCIs in shared autonomy.
  • To investigate user performance and subjective experience with different sensory modalities for robotic control.

Main Methods:

  • Developed comparable auditory and visual interfaces using the oddball paradigm to present choices to users.
Keywords:
brain-computer interfacehuman-robot interactionimitation learningmultitask learningshared autonomy

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  • Users completed a multi-stage robotic manipulation task requiring selection of objects and locations.
  • Collected data on user performance and preferences for each interface modality.

    • Main Results:

    • Users exhibited varying levels of competence and distinct preferences for auditory and visual stimulus modalities.
    • Performance and preference were not uniform across all users, indicating individual differences in BCI modality suitability.
    • The study demonstrated that different users respond differently to auditory and visual feedback in BCI-controlled robotics.

    Conclusions:

    • The choice of sensory modality (auditory vs. visual) significantly impacts user performance and preference in shared autonomy BCIs.
    • Effective human-robot interface design for assistive robotics requires consideration of non-visual modalities.
    • Personalized BCI design, accounting for individual user differences, is crucial for optimizing shared autonomy systems.