Improving the Interaction of Older Adults with a Socially Assistive Table Setting Robot

Olatunji, Samuel; Markfeld, Noa; Gutman, Dana; Givati, Shay; Sarne-Fleischmann, Vardit; Oron-Gilad, Tal; Edan, Yael

doi:10.1007/978-3-030-35888-4_53

Cited by 9 publications

(5 citation statements)

References 26 publications

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“…Ongoing research is aimed at performing studies with older adults for daily living tasks and for nonprofessional users, putting into consideration the influence of demographics on the changes automation brings [64]. LOA has proven to influence performance for older adults [12]. We expect the effect of the levels of workload to amplify with them.…”

Section: Discussionmentioning

confidence: 99%

“…The level of automation (LOA) of the system, defined as the degree to which the robot and the human are involved in the collaborative task [8][9][10][11], influences the characteristics of the dynamics of the collaboration, the behavior of the robots, actions to be taken, as well as autonomy of the human in the collaboration [12,13]. Workload addresses the actual and perceived amount of work that the human operator experiences as related to the effort invested in the task [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Evaluating Levels of Automation in Human–Robot Collaboration at Different Workload Levels

2021

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This study explored how levels of automation (LOA) influence human robot collaboration when operating at different levels of workload. Two LOA modes were designed, implemented, and evaluated in an experimental collaborative assembly task setup for four levels of workload composed of a secondary task and task complexity. A user study conducted involving 80 participants was assessed through two constructs especially designed for the evaluation (quality of task execution and usability) and user preferences regarding the LOA modes. Results revealed that the quality of task execution and usability was better at high LOA for low workload. Most of participants also preferred high LOA when the workload increases. However, when complexity existed within the workload, most of the participants preferred the low LOA. The results reveal the benefits of high and low LOA in different workload situations. This study provides insights related to shared control designs and reveals the importance of considering different levels of workload as influenced by secondary tasks and task complexity when designing LOA in human–robot collaborations.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluating Levels of Automation in Human–Robot Collaboration at Different Workload Levels

2021

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“…The reason for this might be connected with the frustration experienced by the participants in the higher task complexity when the automation failed or did not perform as expected (as seen in the frustration dimension of the NASA-TLX). In these situations, participants switched to lower automation (as was possible in the adjustable-high LOA condition), perhaps to facilitate easier handling of some of these challenges as noted in [29] where a lower LOA was found to better facilitate easier interaction. The switching, however, incurs some switch costs [22,52] which could have contributed to the frustration observed in the high LOA mode.…”

Section: Impact Of Loa In Mrp Systemsmentioning

confidence: 99%

Levels of Automation for a Mobile Robot Teleoperated by a Caregiver

Olatunji

Potenza

Kiselev

et al. 2022

J. Hum.-Robot Interact.

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Caregivers in eldercare can benefit from telepresence robots that allow them to perform a variety of tasks remotely. In order for such robots to be operated effectively and efficiently by non-technical users, it is important to examine if and how the robotic system’s level of automation (LOA) impacts their performance. The objective of this work was to develop suitable LOA modes for a mobile robotic telepresence (MRP) system for eldercare and assess their influence on users’ performance, workload, awareness of the environment, and usability at two different levels of task complexity. For this purpose, two LOA modes were implemented on the MRP platform: assisted teleoperation (low LOA mode) and autonomous navigation (high LOA mode). The system was evaluated in a user study with 20 participants, who, in the role of the caregiver, navigated the robot through a home-like environment to perform control and perception tasks. Results revealed that performance improved in the high LOA when task complexity was low. However, when task complexity increased, lower LOA improved performance. This opposite trend was also observed in the results for workload and situation awareness. We discuss the results in terms of the LOAs’ impact on users’ attitude towards automation and implications on usability.

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“…The reason for this might be connected with the frustration experienced by the participants in the higher task complexity when the automation failed or did not perform as expected (as seen in the frustration dimension of the NASA-TLX). In these situations, participants switched to a lower automation, perhaps to facilitate easier handling of some of these challenges as noted in [48] where a lower LOA was found to better facilitate easier interaction. The switching however incurs some switch costs [49], [29] which could have contributed to the frustration observed in the high LOA mode.…”

Section: A Impact Of Loa In Mrp Systemsmentioning

confidence: 99%

Levels of Automation for a Mobile Robot Teleoperated by a Caregiver

Olatunji¹,

Potenza²,

Kiselev³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Caregivers in eldercare can benefit from telepresence robots that allow them to perform a variety of tasks remotely. In order for such robots to be operated effectively and efficiently by non-technical users, it is important to examine if and how the robotic system's level of automation (LOA) impacts their performance. The objective of this work was to develop suitable LOA modes for a mobile robotic telepresence (MRP) system for eldercare and assess their influence on users' performance, workload, awareness of the environment and usability at two different levels of task complexity. For this purpose, two LOA modes were implemented on the MRP platform: assisted teleoperation (low LOA mode) and autonomous navigation (high LOA mode). The system was evaluated in a user study with 20 participants, who, in the role of the caregiver, navigated the robot through a home-like environment to perform various control and perception tasks. Results revealed that performance improved at high LOA when the task complexity was low. However, when task complexity increased, lower LOA improved performance. This opposite trend was also observed in the results for workload and situation awareness. We discuss the results in terms of the LOAs' impact on users' attitude towards automation and implications on usability.

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Improving the Interaction of Older Adults with a Socially Assistive Table Setting Robot

Cited by 9 publications

References 26 publications

Evaluating Levels of Automation in Human–Robot Collaboration at Different Workload Levels

Evaluating Levels of Automation in Human–Robot Collaboration at Different Workload Levels

Levels of Automation for a Mobile Robot Teleoperated by a Caregiver

Levels of Automation for a Mobile Robot Teleoperated by a Caregiver

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