Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Sing Le

dblp:203/4764 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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.

Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 87% Wearable and physiological sensing · 13%
Artificial intelligence
1 paper
Robot manipulation · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
soft robotics
0.312017
A reconfigurable hybrid actuator with rigid and soft components · ICRA 2017
Health and well-being technologies › rehabilitation
hand rehabilitation
0.312017
A lobster-inspired robotic glove for hand rehabilitation · ICRA 2017
Health and well-being technologies › rehabilitation technology
soft robotic glove
0.312017
A lobster-inspired robotic glove for hand rehabilitation · ICRA 2017
Robotics › Robot manipulation
physical human-robot interaction
0.112017
A reconfigurable hybrid actuator with rigid and soft components · ICRA 2017
Wearable and physiological sensing › electromyography
surface electromyography
0.112017
A lobster-inspired robotic glove for hand rehabilitation · ICRA 2017

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

soft pneumatic actuation · 0.3sEMG pattern learning · 0.3rigid-soft hybrid actuation · 0.3bio-inspired design · 0.3
YearPublicationVenuePosition
2017 A reconfigurable hybrid actuator with rigid and soft components
abstract
Classical rigid-bodied robotic systems are presented with proven success in theoretical development and industrial applications, are recently challenged by the emergence of soft robotics due to a growing need in physical human-robot interactions (pHRI), such as wearable devices, medical robots, personal robots, etc. In this paper, we present the design and fabrication of a robust, hybrid bending actuator build from both rigid and soft components inspired by crustaceans, where its bending radius and axis can be mechanically programmed through the selective activation of the rigid exterior joints, actuated by the soft actuators inside. The hybrid actuator was experimentally measured in terms of bending and force tests to demonstrate the utility of this design. Finally, a case study was presented to demonstrate its capacity to adapt to specific objects geometry, anticipating its potential application in situations where compliance is the priority.
Yaohui Chen 0002, Sing Le, Qiao Chu Tan, Oscar Lau, Fang Wan 0002, Chaoyang Song 0001
ICRA2
2017 A lobster-inspired robotic glove for hand rehabilitation
abstract
This paper presents preliminary results of the design, development, and evaluation of a hand rehabilitation glove fabricated using lobster-inspired hybrid design with rigid and soft components for actuation. Inspired by the bending abdomen of lobsters, hybrid actuators are built with serially jointed rigid shells actuated by pressurized soft chambers inside to generate bending motions. Such bio-inspiration absorbs features from the classical rigid-bodied robotics with preciselydefined motion generation, as well as the emerging soft robotics with light-weight, physically safe, and adaptive actuation. The fabrication procedure is described, followed by experiments to mechanically characterize these actuators. Finally, an open-palm glove design integrated with these hybrid actuators are presented for a qualitative case study. A hand rehabilitation system is developed by learning patterns of the sEMG signals from the users forearm to train the assistive glove for hand rehabilitation exercises.
Yaohui Chen 0002, Sing Le, Qiao Chu Tan, Oscar Lau, Fang Wan 0002, Chaoyang Song 0001
ICRA2