Demo Data from EDBT 2026 / reviewers in the wild / expert
Atsushi Fujimori
dblp:119/9702
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 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 · 87% Motion planning and robot control · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping › mobile robot navigation
local navigation |
0.0 | 1 | 1997 | Adaptive navigation of mobile robots with obstacle avoidance · IEEE Trans. Robotics Autom. 1997 |
Robotics › Robot navigation and mapping
obstacle avoidance |
0.0 | 1 | 1997 | Adaptive navigation of mobile robots with obstacle avoidance · IEEE Trans. Robotics Autom. 1997 |
Robotics › Motion planning and robot control › robot dynamics
mobile robot dynamics |
0.0 | 1 | 1997 | Adaptive navigation of mobile robots with obstacle avoidance · IEEE Trans. Robotics Autom. 1997 |
Methods — techniques the papers use, named apart from their topics
switching control · 0.0differential equation navigation law · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Formation Control of Multiple Mobile Robots with Large Obstacle AvoidanceabstractThis paper presents a formation control of mobile robots with a large obstacle avoidance. The mobile robots considered in this paper have multiple sonars which are used for not only constructing formation but also avoiding obstacle. The novel modules overcoming the drawbacks of the previous navigation algorithm [6] are introduced to accomplish the obstacle avoidance and formation control. The effectiveness of the proposed techniques are demonstrated by an experiment using three mobile robots. Atsushi Fujimori, Atsushi Hosono, Kazuro Takahashi, Shinsuke Oh-hara |
ICARCV | 1 |
| 1997 | Adaptive navigation of mobile robots with obstacle avoidanceabstractA local navigation technique with obstacle avoidance, called adaptive navigation, is proposed for mobile robots in which the dynamics of the robot are taken into consideration. The only information needed about the local environment is the distance between the robot and the obstacles in three specified directions. The navigation law is a first-order differential equation and navigation to the goal and obstacle avoidance are achieved by switching the direction angle of the robot. The effectiveness of the technique is demonstrated by means of simulation examples. Atsushi Fujimori, Peter N. Nikiforuk, Madan M. Gupta |
IEEE Trans. Robotics Autom. | 1 |