Demo Data from SIGIR 2026 / reviewers in the wild / expert
Damien Paillot
dblp:172/3471
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
model predictive control |
0.4 | 1 | 2019 | Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm · ICRA 2019 |
Robotics › Motion planning and robot control › robot control
motion control |
0.4 | 1 | 2019 | Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm · ICRA 2019 |
Robotics › Motion planning and robot control › robot control › optimal control
constrained optimal control |
0.1 | 1 | 2019 | Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm · ICRA 2019 |
Methods — techniques the papers use, named apart from their topics
model predictive control · 0.4constrained optimal control · 0.4braking law · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing AlgorithmabstractThis paper deals with motion control for an 8-degree-of-freedom (DOF) high performance driving simulator. We formulate a constrained optimal control that defines the dynamical behavior of the system. Furthermore, the paper brings together various methodologies for addressing feasibility issues arising in implicit model predictive control-based motion cueing algorithms. The implementation of different techniques is described and discussed subsequently. Several simulations are carried out in the simulator platform. It is observed that the only technique that can provide ensured closed-loop stability by assuring feasibility over all prediction horizons is a braking law that basically saturates the control inputs in the constrained form. Carolina Rengifo, Jean-Rémy Chardonnet, Hakim Mohellebi, Damien Paillot, Andras Kemeny |
ICRA | 4 |