Demo Data from EDBT 2026 / reviewers in the wild / expert
Ouboti Djaneye-Boundjou
dblp:179/9705
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—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 |
Robot manipulation · 33% Motion planning and robot control · 33% 3D vision · 33% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
industrial robot |
0.3 | 1 | 2018 | Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018 |
Robotics › Motion planning and robot control › robot calibration
kinematic calibration |
0.3 | 1 | 2018 | Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018 |
Computer vision › 3D vision › camera calibration
self-calibration |
0.3 | 1 | 2018 | Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018 |
Mathematical optimization
metaheuristic optimization |
0.1 | 1 | 2018 | Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018 |
Mathematical optimization › metaheuristic optimization › swarm intelligence
particle swarm optimization |
0.1 | 1 | 2018 | Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018 |
Methods — techniques the papers use, named apart from their topics
particle swarm optimization · 0.7geometric calibration · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Geometry Based Self Kinematic Calibration Method for Industrial RobotsabstractAccuracy of robots is an important facet in an industrial setting. In this paper, we present a novel kinematic calibration methodology. Traditional calibration techniques require an external metrology device. Unlike those, the presented product here is highly practical in that it does not require a metrology device. The kinematic calibration model is formulated by making use of the robot itself as a metrology device to measure the geometry of a known artifact. The optimal parameters/characteristics of the model are identified using a Particle Swarm Optimization (PSO) technique. Our experimental results show that this new approach provides results comparable to those generated using spatial information provided by a Coordinate Measurement Machine (CMM). Using this new approach (GageCAL), the Yaskawa Motoman “MHS-Hi” robot is calibrated. Our experimental testing also indicates that this methodology can be extended to a wide variety of anthropomorphic robots. Temesguen Messay, George Sutton, Ouboti Djaneye-Boundjou |
ICRA | 3 |