Demo Data from EDBT 2026 / reviewers in the wild / expert
F. Boyer
dblp:09/4870
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2006
—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 |
Motion planning and robot control · 91% Autonomous driving · 9% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › motion planning
kinodynamic planning |
0.1 | 1 | 2006 | Trajectory Deformation applied to Kinodynamic Motion Planning for a Realistic Car Model · ICRA 2006 |
Robotics › Motion planning and robot control
motion planning |
0.1 | 1 | 2006 | Trajectory Deformation applied to Kinodynamic Motion Planning for a Realistic Car Model · ICRA 2006 |
Robotics › Motion planning and robot control › trajectory planning
trajectory deformation |
0.1 | 1 | 2006 | Trajectory Deformation applied to Kinodynamic Motion Planning for a Realistic Car Model · ICRA 2006 |
Methods — techniques the papers use, named apart from their topics
locally linearized dynamic model · 0.1collision avoidance · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | Trajectory Deformation applied to Kinodynamic Motion Planning for a Realistic Car ModelabstractProviding a safe behavior of a vehicle in every situation is a critical mission in the design of a modern car. To measure this ability, the standard ISO double lane change test was a designed by consumer unions. The detailed simulation of such an active safety issue would contribute to shorten the design cycle time of a vehicle by reducing the number of real world tests. In this paper we discuss the use of a trajectory deformation algorithm to determine a possible motion for a realistic dynamic car model going through such a test, and the way to determine the maximum passage speed. The main idea of this method is to iteratively deform the inputs of the system to progressively reduce the number of collisions while respecting the dynamic constraints. This deformation is calculated for each iteration by taking into account a locally linearized dynamic model of the system. Consequently, this algorithm can anticipate correctly the inputs needed to solve the future collisions F. Boyer, Florent Lamiraux |
ICRA | 1 |