Demo Data from EDBT 2026 / reviewers in the wild / expert
Do-Young Yoon
dblp:31/582
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2003
—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 · 77% Motion planning and robot control · 23% |
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
mobile robot navigation |
0.0 | 1 | 2003 | A biologically inspired homeostatic motion controller for autonomous mobile robots · ICRA 2003 |
Robotics › Motion planning and robot control › robot control › nonlinear control
nonlinear feedback control |
0.0 | 1 | 2003 | A biologically inspired homeostatic motion controller for autonomous mobile robots · ICRA 2003 |
Methods — techniques the papers use, named apart from their topics
homeostasis · 0.0behavior-based control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | A biologically inspired homeostatic motion controller for autonomous mobile robotsabstractThis paper proposes an autonomous motion controller for mobile robots. It combines a biologically inspired motion planner and a nonlinear feedback controller in order to make a simple and practical motion controller in natural unknown environments. The motion planner part is designed in the frame of behavior-based scheme and adopts the biological concept "homeostasis". It plays the role of determining desired temporal target posture and modifying controller's gain parameters. The other nonlinear controller part drives the robot to the given target posture from the planner. As a result, the stable nonlinear feedback controller in ideal obstacle free space becomes practical one in natural environments constrained by obstacles. The proposed controller is simple mainly due to its behavior-based characteristics and stable due to the feedback controller considering robot's physical constraints. Simulated results and some experimental feature for autonomous navigation of the differential drive mobile robot, named "MARI", are shown for the present. Do-Young Yoon, Sang-Rok Oh, Gwi-Tae Park, Bum-Jae You |
ICRA | 1 |