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Tien-Sung Chio

dblp:16/867 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2006
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1Applied, interdisciplinary, general and emerging computing · 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 · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › multi-robot systems
multi-robot team
0.012003
Rules and control strategies of multi-robot team moving in hierarchical formation · ICRA 2003
Knowledge, reasoning and agents › Multi-agent systems
formation control
0.012003
Rules and control strategies of multi-robot team moving in hierarchical formation · ICRA 2003

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

hybrid architecture · 0.0control law derivation · 0.0
YearPublicationVenuePosition
2006 Multi-Agent Online Work Dispatching Control for a Multi-Facility Manufacturing System
abstract
In this paper, we formulate the multi-facility dispatching problems as a discrete event modular feedback control problem which is based on a thorough mathematical structure. A simulation experiment shows that our proposed real-time state feedback control scheme improves the multi-facility manufacturing system performance in terms a measure of order lateness.
Yenming J. Chen, Tien-Sung Chio
SMC2
2003 Rules and control strategies of multi-robot team moving in hierarchical formation
abstract
The main objective of this paper is to study the control problems for a multi-robot team moving in hierarchical formation. We formulate the problem as a chart by the four-tier hybrid architecture. We devise rules to form a realizable hierarchical formation. Four control laws are derived to achieve the formation patterns. The proposed control laws are suitable for the on-line, real-time formation tasks. Simulation result shows the efficacy of the approaches.
Tien-Sung Chio, Tzyh Jong Tarn
ICRA1