Demo Data from SIGIR 2026 / reviewers in the wild / expert
Michael Drossakis
dblp:151/9499
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
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 |
Motion planning and robot control · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control › sensor-based control › visual servoing
image-based visual servoing |
0.2 | 1 | 2014 | Robustness analysis of model predictive control for constrained Image-Based Visual Servoing · ICRA 2014 |
Robotics › Motion planning and robot control › robot control
model predictive control |
0.2 | 1 | 2014 | Robustness analysis of model predictive control for constrained Image-Based Visual Servoing · ICRA 2014 |
Robotics › Motion planning and robot control › robot control › robust control
robustness analysis |
0.2 | 1 | 2014 | Robustness analysis of model predictive control for constrained Image-Based Visual Servoing · ICRA 2014 |
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing |
0.2 | 1 | 2014 | Robustness analysis of model predictive control for constrained Image-Based Visual Servoing · ICRA 2014 |
Methods — techniques the papers use, named apart from their topics
nonlinear model predictive control · 0.2input-to-state stability analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Robustness analysis of model predictive control for constrained Image-Based Visual ServoingabstractIn this paper, robustness analysis of constrained Image Based Visual Servoing based on Nonlinear Model Predictive Control (NMPC) is presented. It is known, that real applications such an aerial or a fast underwater robotic systems, suffer from the presence of external disturbances. These kinds of disturbances are inevitable in the physical systems, so it is of great interest to employ robust controllers. Therefore, a rigorous robustness analysis should be conducted. In this paper, the Image Based Visual Servoing system under the MPC framework is proven to be Input-to-State Stable (ISS) and a permissible upper bound of the disturbances is provided. Finally, the validity of the theoretic results is illustrated through a simulated example. Shahab Heshmati-Alamdari, George K. Karavas, Alina Eqtami, Michael Drossakis, Kostas J. Kyriakopoulos |
ICRA | 4 |