Demo Data from SIGIR 2026 / reviewers in the wild / expert
David F. Brochero Giraldo
dblp:416/5800
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 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 |
Robot navigation and mapping · 44% Multi-agent systems · 44% Motion planning and robot control · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
multi-robot navigation |
0.9 | 1 | 2025 | Safe Radial Segregation Algorithm for Swarms of Dubins-Like Robots · ICRA 2025 |
Knowledge, reasoning and agents › Multi-agent systems
swarm robotics |
0.9 | 1 | 2025 | Safe Radial Segregation Algorithm for Swarms of Dubins-Like Robots · ICRA 2025 |
Robotics › Motion planning and robot control
collision avoidance |
0.3 | 1 | 2025 | Safe Radial Segregation Algorithm for Swarms of Dubins-Like Robots · ICRA 2025 |
Methods — techniques the papers use, named apart from their topics
radial segregation · 0.9dubins-like robot control · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Safe Radial Segregation Algorithm for Swarms of Dubins-Like RobotsabstractThis work addresses the problem of radially segregating heterogeneous robotic swarms. Such swarms are those composed of different groups of robots. Unlike other works on segregation in the literature, we propose a controller for Dubins-like robots, motivated by autonomous aerial, wheeled, and underwater vehicles. Our controller can drive the robots individually to converge to circles that are shared only by robots of the same group. We present a heuristic and a collision avoidance scheme in which the information required is locally acquired. We present several simulations widely varying the number of robots per group and the number of groups in which segregation is always reached and collisions between robots are always avoided. Edson B. F. Filho, David F. Brochero Giraldo, Arthur H. D. Nunes, Luciano C. A. Pimenta |
ICRA | 2 |