Safety Assessment Review of a Dressing Assistance Robot
Hazard analysis methods such as HAZOP and STPA have proven to be effective methods for assurance of system safety for years. However, the dimensionality and human factors uncertainty of many assistive robotic applications challenges the capability of these methods to provide comprehensive coverage o...
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| Published in: | Frontiers in robotics and AI Vol. 8; p. 667316 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Frontiers Media S.A
14-06-2021
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Hazard analysis methods such as HAZOP and STPA have proven to be effective methods for assurance of system safety for years. However, the dimensionality and human factors uncertainty of many assistive robotic applications challenges the capability of these methods to provide comprehensive coverage of safety issues from interdisciplinary perspectives in a timely and cost-effective manner. Physically assistive tasks in which a range of dynamic contexts require continuous human–robot physical interaction such as e.g., robot-assisted dressing or sit-to-stand pose a new paradigm for safe design and safety analysis methodology. For these types of tasks, considerations have to be made for a range of dynamic contexts where the robot-assistance requires close and continuous physical contact with users. Current regulations mainly cover industrial collaborative robotics regarding physical human–robot interaction (pHRI) but largely neglects direct and continuous physical human contact. In this paper, we explore limitations of commonly used safety analysis techniques when applied to robot-assisted dressing scenarios. We provide a detailed analysis of the system requirements from the user perspective and consider user-bounded hazards that can compromise safety of this complex pHRI. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Noman Naseer, Air University, Pakistan Ying Feng, South China University of Technology, China Reviewed by: Paolo Fiorini, University of Verona, Italy This article was submitted to Biomedical Robotics, a section of the journal Frontiers in Robotics and AI |
| ISSN: | 2296-9144 2296-9144 |
| DOI: | 10.3389/frobt.2021.667316 |