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Sean Taylor

dblp:340/7625 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2024
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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%
Computer graphics and multimedia
1 paper
Computational fabrication · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
robotic hand
0.812024
Fully 3D printable Robot Hand and Soft Tactile Sensor based on Air-pressure and Capacitive Proximity Sensing · ICRA 2024
Robotics › Robot manipulation › robotic hand
soft robotic hand
0.812024
Fully 3D printable Robot Hand and Soft Tactile Sensor based on Air-pressure and Capacitive Proximity Sensing · ICRA 2024
Robotics › Robot manipulation › tactile sensing › tactile sensor design
soft tactile sensor
0.812024
Fully 3D printable Robot Hand and Soft Tactile Sensor based on Air-pressure and Capacitive Proximity Sensing · ICRA 2024
Robotics › Robot manipulation
tactile sensing
0.812024
Fully 3D printable Robot Hand and Soft Tactile Sensor based on Air-pressure and Capacitive Proximity Sensing · ICRA 2024
Computational fabrication
additive manufacturing
0.212024
Fully 3D printable Robot Hand and Soft Tactile Sensor based on Air-pressure and Capacitive Proximity Sensing · ICRA 2024
Computational fabrication › additive manufacturing
multi-material 3d printing
0.212024
Fully 3D printable Robot Hand and Soft Tactile Sensor based on Air-pressure and Capacitive Proximity Sensing · ICRA 2024

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

capacitive sensing · 1.5air-pressure sensing · 0.8air pressure sensing · 0.8
YearPublicationVenuePosition
2024 Fully 3D printable Robot Hand and Soft Tactile Sensor based on Air-pressure and Capacitive Proximity Sensing
abstract
Soft tactile sensors can enable robots to grasp objects easily and stably by simultaneously providing tactile data and mechanical compliance to robotic hands. If there are low-cost and easy-to-build robotic hands equipped with soft tactile sensors, they would be highly accessible and facilitate many robotics projects. To this end, we propose an accessible robot hand capable of tactile sensing, which can be produced through digital fabrication. We made the robot hand using commercial servo motors as well as components 3D printed from PETG, TPU, and conductive TPU. These materials allow the robot hand to have a soft, durable, and even functional structure. Specifically, the soft fingertip was crafted from TPU and conductive TPU, and their mechanical and electrical properties enable easy implementation of tactile sensing capabilities, such as force and capacitive touch, simply by adding off-the-shelf sensors (air-pressure and capacitance). The proposed robot hand could effectively sense interaction forces and proximity to conductive objects, and its utilization in various tasks was also demonstrated successfully.
Sean Taylor, Kyungseo Park, Sankalp Yamsani, Joohyung Kim
ICRA1
2023 Orthrus: A Dual-arm Quadrupedal Robot for Mobile Manipulation and Entertainment Applications
abstract
In this paper, we present an add-on system that enhances the capabilities of a quadrupedal robot. The addon system efficiently allows the integration of two 6-DOF manipulators with a quadruped as a single system. The design of the system is developed with modularity as an important principle, allowing for versatility and adaptability in various applications of mobile manipulation. With the modular design, the system can easily be used for mobile-manipulation tasks but also as a system for human entertainment. We show the modular and versatility of the system through applications in a home setting and various entertainment settings. The proposed system leads to an enhanced level of human-robot interaction with more engaging and interactive experiences.
Sankalp Yamsani, Sean Taylor, Kazuki Shin, Jooyoung Hong, Dhruv C. Mathur, Kevin G. Gim, Joohyung Kim
RO-MAN2