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Is More Autonomy Always Better?: Exploring Preferences of Users with Mobility Impairments in Robot-assisted Feeding

Authors:

Tapomayukh Bhattacharjee,

Ethan K. Gordon,

Rosario Scalise,

Maria E. Cabrera,

Siddhartha S. SrinivasaAuthors Info & Claims

HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction

Pages 181 - 190

https://doi.org/10.1145/3319502.3374818

Published: 09 March 2020 Publication History

Abstract

A robot-assisted feeding system can potentially help a user with upper-body mobility impairments eat independently. However, autonomous assistance in the real world is challenging because of varying user preferences, impairment constraints, and possibility of errors in uncertain and unstructured environments. An autonomous robot-assisted feeding system needs to decide the appropriate strategy to acquire a bite of hard-to-model deformable food items, the right time to bring the bite close to the mouth, and the appropriate strategy to transfer the bite easily. Our key insight is that a system should be designed based on a user's preference about these various challenging aspects of the task. In this work, we explore user preferences for different modes of autonomy given perceived error risks and also analyze the effect of input modalities on technology acceptance. We found that more autonomy is not always better, as participants did not have a preference to use a robot with partial autonomy over a robot with low autonomy. In addition, participants' user interface preference changes from voice control during individual dining to web-based during social dining. Finally, we found differences on average ratings when grouping the participants based on their mobility limitations (lower vs. higher) that suggests that ratings from participants with lower mobility limitations are correlated with higher expectations of robot performance.

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Cited By

Nanavati ARanganeni VCakmak M(2024)Physically Assistive Robots: A Systematic Review of Mobile and Manipulator Robots That Physically Assist People with DisabilitiesAnnual Review of Control, Robotics, and Autonomous Systems10.1146/annurev-control-062823-0243527:1(123-147)Online publication date: 10-Jul-2024
https://doi.org/10.1146/annurev-control-062823-024352
Babel FHock PWinkle KTorre IZiemke TGrollman DBroadbent EJu WSoh HWilliams T(2024)The Human Behind the Robot: Rethinking the Low Social Status of Service RobotsCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640763(1-10)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610978.3640763
Barrué CSuárez AInzitari MRibera AAlenyà GGrollman DBroadbent EJu WSoh HWilliams T(2024)NYAM: The Role of Configurable Engagement Strategies in Robotic-Assisted FeedingCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640691(228-232)Online publication date: 11-Mar-2024
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Is More Autonomy Always Better?: Exploring Preferences of Users with Mobility Impairments in Robot-assisted Feeding

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cover image ACM Conferences

HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction

March 2020

690 pages

ISBN:9781450367462

DOI:10.1145/3319502

General Chairs:
Tony Belpaeme
Ghent University, Belgium
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James Young
University of Manitoba, Canada
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Program Chairs:
Hatice Gunes
University of Cambridge, UK
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Laurel Riek
UC San Diego, USA

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Published: 09 March 2020

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Nanavati ARanganeni VCakmak M(2024)Physically Assistive Robots: A Systematic Review of Mobile and Manipulator Robots That Physically Assist People with DisabilitiesAnnual Review of Control, Robotics, and Autonomous Systems10.1146/annurev-control-062823-0243527:1(123-147)Online publication date: 10-Jul-2024
https://doi.org/10.1146/annurev-control-062823-024352
Babel FHock PWinkle KTorre IZiemke TGrollman DBroadbent EJu WSoh HWilliams T(2024)The Human Behind the Robot: Rethinking the Low Social Status of Service RobotsCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640763(1-10)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610978.3640763
Barrué CSuárez AInzitari MRibera AAlenyà GGrollman DBroadbent EJu WSoh HWilliams T(2024)NYAM: The Role of Configurable Engagement Strategies in Robotic-Assisted FeedingCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640691(228-232)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610978.3640691
Nanavati AGrollman DBroadbent EJu WSoh HWilliams T(2024)Achieving Deployable Autonomy through Customizability and Human-in-the-Loop: A Case Study in Robot-assisted FeedingCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3638356(136-138)Online publication date: 11-Mar-2024
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