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Luciano E. Almeida

dblp:353/6070 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
path planning
0.712023
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
0.712023
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
YearPublicationVenuePosition
2023 Efficiently Approaching Groups of People in a Socially Acceptable Manner in Environments with Obstacles
abstract
Advancements 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
ICRA2