Demo Data from SIGIR 2026 / reviewers in the wild / expert
Simón Martinez-Rozas
dblp:254/0409
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-3289-3371ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021
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 · 50% Legged, aerial and field robots · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots › aerial robots › unmanned aerial vehicle
tethered aerial robot |
0.5 | 1 | 2021 | Optimization-based Trajectory Planning for Tethered Aerial Robots · ICRA 2021 |
Robotics › Motion planning and robot control
trajectory planning |
0.5 | 1 | 2021 | Optimization-based Trajectory Planning for Tethered Aerial Robots · ICRA 2021 |
Methods — techniques the papers use, named apart from their topics
nonlinear optimization · 0.5multi-objective optimization · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Optimization-based Trajectory Planning for Tethered Aerial RobotsabstractThis paper presents a non-linear optimization method for trajectory planning of tethered aerial robots. Particularly, the paper addresses the planning problem of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) by means of a tether. The result is a collision-free trajectory for UAV and tether, assuming the UGV position is static. The optimizer takes into account constraints related to the UAV, UGV and tether positions, obstacles and temporal aspects of the motion such as limited robot velocities and accelerations, and finally the tether state, which is not required to be tense. The problem is formulated in a weighted multi-objective optimization framework. Results from simulated scenarios demonstrate that the approach is able to generate obstacle-free and smooth trajectories for the UAV and tether. Simón Martinez-Rozas, David Alejo, Fernando Caballero, Luis Merino |
ICRA | 1 |