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David F. Brochero Giraldo

dblp:416/5800 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
multi-robot navigation
0.912025
Safe Radial Segregation Algorithm for Swarms of Dubins-Like Robots · ICRA 2025
Knowledge, reasoning and agents › Multi-agent systems
swarm robotics
0.912025
Safe Radial Segregation Algorithm for Swarms of Dubins-Like Robots · ICRA 2025
Robotics › Motion planning and robot control
collision avoidance
0.312025
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
YearPublicationVenuePosition
2025 Safe Radial Segregation Algorithm for Swarms of Dubins-Like Robots
abstract
This 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
ICRA2