Demo Data from SIGIR 2026 / reviewers in the wild / expert
In-Soo Jeong
dblp:64/353
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2001
—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 |
Robot navigation and mapping · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping › localization
robot localization |
0.0 | 1 | 2001 | Self-localization for Mobile Robots by Matching Two Consecutive Environmental Range Data · ICRA 2001 |
Robotics › Robot navigation and mapping › mobile robot perception
omnidirectional perception |
0.0 | 1 | 2001 | Self-localization for Mobile Robots by Matching Two Consecutive Environmental Range Data · ICRA 2001 |
Methods — techniques the papers use, named apart from their topics
scan matching · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Self-localization for Mobile Robots by Matching Two Consecutive Environmental Range DataabstractWhile navigating, most autonomous mobile robots view things only in front of them and, as a result, they may collide with objects moving from the side or behind. To overcome this problem, an active omni-directional range sensor system is presented, that is capable of obtaining the omni-directional range data on a navigation environment through the use of a laser conic plane and a conic mirror. Based on this system configuration, we propose a self-localization algorithm. The proposed algorithm to estimate the current position and heading angle of mobile robots utilizes the registered range data obtained at two positions; current and previous and matches the two range informations. To show the effectiveness of the proposed algorithm, a series of simulations was conducted under various navigation conditions. The results show that the proposed algorithm is very efficient in processing, and can be effectively utilized for self-localization of mobile robots in unknown environments. In-Soo Jeong, Hyung Suck Cho |
ICRA | 1 |