Demo Data from SIGIR 2026 / reviewers in the wild / expert
Anubhav Guha
dblp:203/4932
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved
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 · 100% | |
| Computer networks
1 paper |
Wireless sensing and localization · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
miniature robot |
0.3 | 1 | 2017 | Autonomous locomotion of a miniature, untethered origami robot using hall effect sensor-based magnetic localization · ICRA 2017 |
Methods — techniques the papers use, named apart from their topics
magnetic actuation · 0.6closed-loop position feedback control · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Autonomous locomotion of a miniature, untethered origami robot using hall effect sensor-based magnetic localizationabstractAutonomous control of magnetically-actuated miniature robots enables greater versatility and complexity in function but has so far been a challenge to implement. In this paper, we present closed-loop position feedback control of a miniature origami robot utilizing its integrated magnet and an array of Hall effect sensors, enabling the robot's actuation, detection, and locomotion to be initiated from outside its body. An array of 33 Hall effect sensors arranged in repeated triangles cover a range of 60 mm by 75 mm, enabling position detection of the robot with average error of 0.995±0.520 mm. The robot's speed response to applied magnetic field was characterized, and a controller was designed to actuate the robot dependably. We demonstrate autonomous movement of the robot along preplanned paths and the viability of magnetic detection and actuation. Steven Guitron, Anubhav Guha, Shuguang Li 0005, Daniela Rus |
ICRA | 2 |