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Ciarán T. O'Neill

dblp:208/1598 · also Ciarán Tomás O'Neill · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0001-6902-9985ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 87% Legged, aerial and field robots · 13%
Human-computer interaction and pervasive computing
1 paper
Accessibility and assistive technology · 44% Health and well-being technologies · 44% Human-robot interaction · 13%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › actuation
artificial muscle
0.412019
Robotic Artificial Muscles: Current Progress and Future Perspectives · IEEE Trans. Robotics 2019
Robotics › Robot manipulation › robot actuation
robot actuator
0.412019
Robotic Artificial Muscles: Current Progress and Future Perspectives · IEEE Trans. Robotics 2019
Accessibility and assistive technology
assistive technology
0.412019
Soft Robotic Glove with Integrated Sensing for Intuitive Grasping Assistance Post Spinal Cord Injury · ICRA 2019
Health and well-being technologies › rehabilitation technology
soft robotic glove
0.412019
Soft Robotic Glove with Integrated Sensing for Intuitive Grasping Assistance Post Spinal Cord Injury · ICRA 2019
Robotics › Legged, aerial and field robots
bio-inspired robot
0.112019
Robotic Artificial Muscles: Current Progress and Future Perspectives · IEEE Trans. Robotics 2019

Methods — techniques the papers use, named apart from their topics

state machine intent detection · 0.4shape memory alloy · 0.4dielectric elastomers · 0.4capacitive sensing · 0.4
YearPublicationVenuePosition
2019 Soft Robotic Glove with Integrated Sensing for Intuitive Grasping Assistance Post Spinal Cord Injury
abstract
This paper presents a fully-integrated soft robotic glove with multi-articular textile actuators, custom soft sensors, and an intuitive state machine intent detection controller. We demonstrate that the pressurized actuators can generate motion and force comparable to natural human fingers through bench-top testing. We apply textile-elastomer capacitive sensors to the glove to track finger flexion via strain and detect contact with objects via force. Intuitive user control is achieved via a state machine controller based on signals from the integrated sensors to detect relative changes in hand-object interactions. Results from an initial evaluation with 3 participants with spinal cord injury (SCI), of varied injury levels and years since injury, wearing and controlling the glove show an average of 87% improvement in grasping force, and improvements in functional assessments for participants with recent injuries. A significant variation in response suggests further investigation is required to understand the adaptation needed across different injury levels and durations since injury. Additionally, we evaluate the controller and find an average of 3 seconds from user initiations to completed grasps, and 10% inadvertent grasp triggers and no false releases when objects are held.
Yu Meng Zhou, Diana Wagner, Kristin Nuckols, Roman Heimgartner, Carolina Correia, Megan E. Clarke, Dorothy Orzel, Ciarán T. O'Neill, Ryan Solinsky, Sabrina Paganoni, Conor J. Walsh
ICRA8
2019 Robotic Artificial Muscles: Current Progress and Future Perspectives
abstract
Robotic artificial muscles are a subset of artificial muscles that are capable of producing biologically inspired motions useful for robot systems, i.e., large power-to-weight ratios, inherent compliance, and large range of motions. These actuators, ranging from shape memory alloys to dielectric elastomers, are increasingly popular for biomimetic robots as they may operate without using complex linkage designs or other cumbersome mechanisms. Recent achievements in fabrication, modeling, and control methods have significantly contributed to their potential utilization in a wide range of applications. However, no survey paper has gone into depth regarding considerations pertaining to their selection, design, and usage in generating biomimetic motions. In this paper, we discuss important characteristics and considerations in the selection, design, and implementation of various prominent and unique robotic artificial muscles for biomimetic robots, and provide perspectives on next-generation muscle-powered robots.
Jun Zhang 0025, Jun Sheng, Ciarán T. O'Neill, Conor J. Walsh, Robert J. Wood, Jee-Hwan Ryu, Jaydev P. Desai, Michael C. Yip
IEEE Trans. Robotics3