Alessandro Arsie

dblp:14/2520 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

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
Multi-agent systems · 56% Robot navigation and mapping · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
coverage control
0.112009
Equitable partitioning policies for robotic networks · ICRA 2009
Knowledge, reasoning and agents › Multi-agent systems
multi-robot systems
0.112009
Equitable partitioning policies for robotic networks · ICRA 2009
Knowledge, reasoning and agents › Multi-agent systems
distributed algorithms
0.012009
Equitable partitioning policies for robotic networks · ICRA 2009

Methods — techniques the papers use, named apart from their topics

power diagram · 0.1lloyd algorithm · 0.1
YearPublicationVenuePosition
2009 Equitable partitioning policies for robotic networks
abstract
The most widely applied resource allocation strategy is to balance, or equalize, the total workload assigned to each resource. In mobile multi-agent systems, this principle directly leads to equitable partitioning policies in which (i) the workspace is divided into subregions of equal measure, (ii) there is a bijective correspondence between agents and subregions, and (iii) each agent is responsible for service requests originating within its own subregion. In this paper, we provide the first distributed algorithm that provably allows m agents to converge to an equitable partition of the workspace, from any initial configuration, i.e., globally. Our approach is related to the classic Lloyd algorithm, and provides novel insights into the properties of power diagrams. Simulation results are presented and discussed.
Marco Pavone 0001, Alessandro Arsie, Emilio Frazzoli, Francesco Bullo
ICRA2