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Leyre Aldama

dblp:16/7737 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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 · 100%

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

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems
multi-robot systems
0.112009
Simultaneous task subdivision and allocation for teams of heterogeneous robots · ICRA 2009
Knowledge, reasoning and agents › Multi-agent systems › automated negotiation
negotiation protocol
0.112009
Simultaneous task subdivision and allocation for teams of heterogeneous robots · ICRA 2009
Knowledge, reasoning and agents › Multi-agent systems
task allocation
0.112009
Simultaneous task subdivision and allocation for teams of heterogeneous robots · ICRA 2009

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

rubinstein's alternate offers protocol · 0.1heuristic search · 0.1
YearPublicationVenuePosition
2009 Simultaneous task subdivision and allocation for teams of heterogeneous robots
abstract
In this paper, we present a negotiation protocol for simultaneous task subdivision and allocation for heterogeneous multi-robot systems. An abstraction of the concept of task is presented that allows to apply the protocol on a variety of tasks. The negotiation adopts Rubinstein's alternate offers protocol, where offers are evaluated and generated using a heuristic search step. The protocol has been tested on computer simulations.
Claudio Rossi 0001, Leyre Aldama, Antonio Barrientos
ICRA2
2009 Negotiation of target points for teams of heterogeneous robots: an application to exploration
abstract
In this paper, we present an application to Search and Rescue of a task negotiation protocol for teams of heterogeneous robots. Self-organization through autonomous negotiations allow the robots to assign themselves a number of target observation points decided by the operator, who is relieved from deciding the optimal assignment. The operator can then focus on monitoring the mission and deciding next actions. The protocol has been tested on both computer simulations and real robots.
Claudio Rossi 0001, Leyre Aldama, Antonio Barrientos, Alberto Valero-Gomez
IROS2