Demo Data from EDBT 2026 / reviewers in the wild / expert
Kai-Chong Lei
dblp:353/5756
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—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% | |
| Human-computer interaction and pervasive computing
1 paper |
Haptics and multimodal interaction · 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
soft robotics |
0.7 | 1 | 2023 | STEV: Stretchable Triboelectric E-skin enabled Proprioceptive Vibration Sensing for Soft Robot · ICRA 2023 |
Robotics › Robot manipulation › soft robotics
soft robot proprioception |
0.7 | 1 | 2023 | STEV: Stretchable Triboelectric E-skin enabled Proprioceptive Vibration Sensing for Soft Robot · ICRA 2023 |
Haptics and multimodal interaction
tactile sensing |
0.7 | 1 | 2023 | STEV: Stretchable Triboelectric E-skin enabled Proprioceptive Vibration Sensing for Soft Robot · ICRA 2023 |
Robotics › Robot manipulation
grasping |
0.2 | 1 | 2023 | STEV: Stretchable Triboelectric E-skin enabled Proprioceptive Vibration Sensing for Soft Robot · ICRA 2023 |
Robotics › Robot manipulation › grasping
soft gripper |
0.2 | 1 | 2023 | STEV: Stretchable Triboelectric E-skin enabled Proprioceptive Vibration Sensing for Soft Robot · ICRA 2023 |
Methods — techniques the papers use, named apart from their topics
triboelectric sensing · 1.3liquid metal · 1.3kirigami design · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | STEV: Stretchable Triboelectric E-skin enabled Proprioceptive Vibration Sensing for Soft RobotabstractVibration perception is essential for robotic sensing and dynamic control. Nevertheless, due to the rigorous demand for sensor conformability and stretchability, enabling soft robots with proprioceptive vibration sensing remains challenging. This paper proposes a novel liquid metal-based stretchable e-skin via a kirigami-inspired design to enable soft robot proprioceptive vibration sensing. The e-skin is fabricated into 0.1mm ultrathin thickness, ensuring its negligible influence on the overall stiffness of the soft robot. Moreover, the working mechanism of the e-skin is based on the ubiquitous triboelectrification effect, which transduces mechanical stimuli without external power supply. To demonstrate the practicability of the e-skin, we built a soft gripper consisting of three soft robotic fingers with proprioceptive vibration sensing. Our experiment shows that the gripper can accurately distinguish the grain category (six grains with the same mass, 99.9% accuracy) and the packaging quality (100% accuracy) by simply shaking the gripped bottle. In summary, a soft robotic proprioceptive vibration sensing solution is proposed; it helps soft robots to have a more comprehensive awareness of their self-state and may inspire further research on soft robotics. Kai-Chong Lei, Huaze Tang, Shoujie Li, Yuan Dai, Wenbo Ding 0001, Xiao-Ping Zhang 0002 |
ICRA | 2 |