Demo Data from EDBT 2026 / reviewers in the wild / expert
Mathilda Kitzmann
dblp:357/1207
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—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 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
dexterous manipulation |
0.8 | 1 | 2024 | DenseTact-Mini: An Optical Tactile Sensor for Grasping Multi-Scale Objects From Flat Surfaces · ICRA 2024 |
Robotics › Robot manipulation
grasping |
0.8 | 1 | 2024 | DenseTact-Mini: An Optical Tactile Sensor for Grasping Multi-Scale Objects From Flat Surfaces · ICRA 2024 |
Robotics › Robot manipulation › grasping › soft robotic grasping
soft-fingered grasping |
0.8 | 1 | 2024 | DenseTact-Mini: An Optical Tactile Sensor for Grasping Multi-Scale Objects From Flat Surfaces · ICRA 2024 |
Robotics › Robot manipulation › tactile sensing › tactile sensor design
optical tactile sensor |
0.2 | 1 | 2024 | DenseTact-Mini: An Optical Tactile Sensor for Grasping Multi-Scale Objects From Flat Surfaces · ICRA 2024 |
Robotics › Robot manipulation
tactile sensing |
0.2 | 1 | 2024 | DenseTact-Mini: An Optical Tactile Sensor for Grasping Multi-Scale Objects From Flat Surfaces · ICRA 2024 |
Methods — techniques the papers use, named apart from their topics
fingernail rolling contact · 0.8adhesion force grasping · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | DenseTact-Mini: An Optical Tactile Sensor for Grasping Multi-Scale Objects From Flat SurfacesabstractDexterous manipulation, especially of small daily objects, continues to pose complex challenges in robotics. This paper introduces the DenseTact-Mini, an optical tactile sensor with a soft, rounded, smooth gel surface and compact design equipped with a synthetic fingernail. We propose three distinct grasping strategies: tap grasping using adhesion forces such as electrostatic and van der Waals, fingernail grasping leveraging rolling/sliding contact between the object and fingernail, and fingertip grasping with two soft fingertips. Through comprehensive evaluations, the DenseTact-Mini demonstrates a lifting success rate exceeding 90.2% when grasping various objects, including items such as 1mm basil seeds, thin paperclips, and items larger than 15mm such as bearings. This work demonstrates the potential of soft optical tactile sensors for dexterous manipulation and grasping. Won Kyung Do, Ankush Kundan Dhawan, Mathilda Kitzmann, Monroe Kennedy III |
ICRA | 3 |