Demo Data from EDBT 2026 / reviewers in the wild / expert
Luciano E. Almeida
dblp:353/6070
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved
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 |
Motion planning and robot control · 50% Robot navigation and mapping · 50% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control
path planning |
0.7 | 1 | 2023 | Efficiently Approaching Groups of People in a Socially Acceptable Manner in Environments with Obstacles · ICRA 2023 |
Robotics › Robot navigation and mapping › social navigation
socially-aware path planning |
0.7 | 1 | 2023 | Efficiently Approaching Groups of People in a Socially Acceptable Manner in Environments with Obstacles · ICRA 2023 |
Methods — techniques the papers use, named apart from their topics
social probabilistic roadmap · 1.3set orienteering problem · 1.3f-formation modeling · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Efficiently Approaching Groups of People in a Socially Acceptable Manner in Environments with ObstaclesabstractAdvancements in mobile robotics have allowed humans and robots to interact in different environments and ways. A problem of great interest in Human-Robot Interaction is how to approach individuals, e.g., to gather information, in a socially acceptable manner. We present a new method for planning sequential visits to various groups of people in cluttered environments. The problem is formulated as a Set Orienteering Problem, where each group denotes a cluster with a set of possible approaching points considering different F-formations. We use the concept of a social probabilistic roadmap to determine safe paths between groups. Simulations considering different cases show that methodology produces efficient tours that maximize the number of approached individuals while respecting social norms of distance and a limited budget. Aline F. F. Silva, Luciano E. Almeida, Douglas G. Macharet |
ICRA | 2 |