Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jennifer Petrosino
dblp:300/4715
· DBLP profile ↗
1ranked-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 · 1Systems, architecture and hardware · 1
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 |
Legged, aerial and field robots · 67% Robot manipulation · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › robot design
bio-inspired robot design |
0.3 | 1 | 2017 | Biological undulation inspired swimming robot · ICRA 2017 |
Robotics › Legged, aerial and field robots › underwater robotics
swimming robot |
0.3 | 1 | 2017 | Biological undulation inspired swimming robot · ICRA 2017 |
Robotics › Legged, aerial and field robots
undulatory locomotion |
0.3 | 1 | 2017 | Biological undulation inspired swimming robot · ICRA 2017 |
Methods — techniques the papers use, named apart from their topics
dynamic modeling · 0.3PD control · 0.3CPG-based control · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Biological undulation inspired swimming robotabstractAquatic animal movement results from a complex balance between muscular actuation, swimmer's inertia, damping, and stiffness; as well as, the effects from the fluid environment. Most aquatic animals utilize undulatory propulsion methods during swimming. Propulsion mode transition involves a variation of these parameters, and to better investigate the variation of these parameters during propulsion mode switching, and provide guidance for swimming robot design, we studied propulsion mechanism of undulation locomotion by combining biological investigation, mathematical simulation and experimental validation. A modular robot platform, with assembling function, was built based on the obtained biological features to realize the corresponding propulsion methods. Then a modular dynamic modeling method was proposed to simulate robot locomotion using a CPG based algorithm and a PD control method, further revealing the underlying mechanism for undulatory locomotion. Finally, experiments were conducted using the robotic platform to validate the found conclusions as well as enhance the propulsion mechanism of undulatory motion, providing a generic guidance for swimming robot design. Zongyao Chen, Jennifer Petrosino, William R. Hamel |
ICRA | 3 |