research-article

Survey of domain-specific performance measures in assistive robotic technology

Authors:

Katherine M. Tsui,

Holly A. Yanco,

David J. Feil-Seifer,

Maja J. MatarićAuthors Info & Claims

PerMIS '08: Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems

Pages 116 - 123

https://doi.org/10.1145/1774674.1774693

Published: 19 August 2008 Publication History

Abstract

Assistive robotics have been developed for several domains, including autism, eldercare, intelligent wheelchairs, assistive robotic arms, external limb prostheses, and stroke rehabilitation. Work in assistive robotics can be divided into two larger research areas: technology development, where new devices, software, and interfaces are created; and clinical application, where assistive technology is applied to a given end-user population. Moving from technology development towards clinical applications is a significant challenge. Developing performance metrics for assistive robots can unveil a larger set of challenges. For example, what well established performance measures should be used for evaluation to lend credence to a particular assistive robotic technology from a clinician's perspective? In this paper, we survey several areas of assistive robotic technology in order to demonstrate domain-specific means for evaluating the performance of an assistive robot system.

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Camilleri ADogramadzi SCaleb-Solly P(2022)Learning from Carers to inform the Design of Safe Physically Assistive Robots - Insights from a Focus Group Study2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI)10.1109/HRI53351.2022.9889658(703-707)Online publication date: 7-Mar-2022
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Survey of domain-specific performance measures in assistive robotic technology
1. General and reference
  1. Document types
    1. Surveys and overviews

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PerMIS '08: Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems

August 2008

333 pages

ISBN:9781605582931

DOI:10.1145/1774674

Conference Chairs:
Raj Madhavan
Oak Ridge National Laboratory/NIST
,
Elena Messina
Intelligent Systems Division, NIST

Copyright © 2008 ACM.

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https://dl.acm.org/doi/10.5555/3523760.3523859
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https://doi.org/10.1109/HRI53351.2022.9889658
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https://dl.acm.org/doi/10.1145/3434780.3436545
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