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Ciaran ONeill

dblp:416/5999 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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 · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › tactile sensing › contact sensing
contact detection
0.912025
Force Admittance Control of an Underactuated Gripper with Full-State Feedback · ICRA 2025
Robotics › Robot manipulation
grasping
0.912025
Force Admittance Control of an Underactuated Gripper with Full-State Feedback · ICRA 2025
Robotics › Robot manipulation › grasping
underactuated grasping
0.912025
Force Admittance Control of an Underactuated Gripper with Full-State Feedback · ICRA 2025
Robotics › Robot manipulation › grasping › underactuated grasping
underactuated gripper
0.312025
Force Admittance Control of an Underactuated Gripper with Full-State Feedback · ICRA 2025

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

pneumatic rolling diaphragm actuator · 0.9full state feedback · 0.9admittance control · 0.9
YearPublicationVenuePosition
2025 Force Admittance Control of an Underactuated Gripper with Full-State Feedback
abstract
We present admittance control and fingertip contact detection with a linkage gripper remotely driven by a pneumatic rolling diaphragm actuator. The gripper is driven by underactuated mechanisms sensorized by joint encoders in order to fully determine the gripper state. We present the modelling of the linkage and fluidic transmission, validate its ability to regulate pinch force via admittance control within an RMS error well under 0.5 Newtons, and show the ability to detect contact at targeted locations on the linkage. In addition, we demonstrate simple grasping behaviors: blindly searching for an unobstructed object and detecting object loss. Our results show that an integrative approach of instrumenting underactuated gripper mechanisms can result in a lightweight gripper that is not only mechanically adaptive but sensitive enough to react to contact events without distal sensors or vision.
Zhi Ern Teoh, Ciaran ONeill, Lael Odhner, John Peter Whitney, Matthew A. Estrada
ICRA4