Demo Data from SIGIR 2026 / reviewers in the wild / expert
Arvind Ananthanarayanan
dblp:116/6501
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
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 · 70% Robot manipulation · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
force sensing |
0.1 | 1 | 2012 | A compact two DOF magneto-elastomeric force sensor for a running quadruped · ICRA 2012 |
Robotics › Legged, aerial and field robots › legged robots
quadruped robot |
0.1 | 1 | 2012 | A compact two DOF magneto-elastomeric force sensor for a running quadruped · ICRA 2012 |
Robotics › Legged, aerial and field robots › legged robots
quadruped running |
0.1 | 1 | 2012 | A compact two DOF magneto-elastomeric force sensor for a running quadruped · ICRA 2012 |
Robotics › Legged, aerial and field robots
ground reaction force measurement |
0.0 | 1 | 2012 | A compact two DOF magneto-elastomeric force sensor for a running quadruped · ICRA 2012 |
Methods — techniques the papers use, named apart from their topics
hall effect sensor · 0.1artificial neural network · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | A compact two DOF magneto-elastomeric force sensor for a running quadrupedabstractThis paper presents a novel design approach for a two-DOF foot force sensor for a high speed running quadruped. The adopted approach harnesses the deformation property of an elastomeric material to relate applied force to measurable deformation. A lightweight, robust and compact magnetic-field based sensing system, consisting of an assembly of miniature hall-effect sensors, is employed to infer the positional information of a magnet embedded in the elastomeric material. Instead of solving two non-linear models (magnetic field and elastomeric) sequentially, a direct approach of using artificial neural networks (ANN) is utilized to relate magnetic flux density (MFD) measurements to applied forces. The force sensor, which weighs only 24.5 gms, provides a measurement range of 0 – 1000 N normal to the ground and up to ± 125N parallel to the ground. The mean force measurement accuracy was found to be within 7% of the applied forces. The sensor designed as part of this work finds direct applications in ground reaction force sensing for a running quadrupedal robot. Arvind Ananthanarayanan, Shaohui Foong, Sangbae Kim |
ICRA | 1 |