EDBT 2026 Demo / reviewers in the wild / expert
Jing-Chen Peng
dblp:359/2364
· DBLP profile ↗
1ranked-venue papers
1as 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 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 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 · 67% Motion planning and robot control · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot dynamics › contact dynamics
contact force analysis |
0.8 | 1 | 2024 | 3D Force and Contact Estimation for a Soft-Bubble Visuotactile Sensor Using FEM · ICRA 2024 |
Robotics › Robot manipulation › force sensing
force estimation |
0.8 | 1 | 2024 | 3D Force and Contact Estimation for a Soft-Bubble Visuotactile Sensor Using FEM · ICRA 2024 |
Robotics › Robot manipulation
tactile sensing |
0.8 | 1 | 2024 | 3D Force and Contact Estimation for a Soft-Bubble Visuotactile Sensor Using FEM · ICRA 2024 |
Methods — techniques the papers use, named apart from their topics
linear plane stress approximation · 0.8finite element method · 0.8RGB-D sensing · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | 3D Force and Contact Estimation for a Soft-Bubble Visuotactile Sensor Using FEMabstractSoft-bubble tactile sensors have the potential to capture dense contact and force information across a large contact surface. However, it is difficult to extract contact forces directly from observing the bubble surface because local contacts change the global surface shape significantly due to membrane mechanics and air pressure. This paper presents a model-based method of reconstructing dense contact forces from the bubble sensor’s internal RGBD camera and air pressure sensor. We present a finite element model of the force response of the bubble sensor that uses a linear plane stress approximation that only requires calibrating 3 variables. Our method is shown to reconstruct normal and shear forces significantly more accurately than the state-of-the-art, with comparable accuracy for detecting the contact patch, and with very little calibration data. Jing-Chen Peng, Shaoxiong Yao, Kris Hauser |
ICRA | 1 |