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Dimitris Theodorakatos

dblp:72/629 · DBLP profile ↗
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1ranked-venue papers
0as 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 · 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% Motion planning and robot control · 44%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
collision avoidance
0.112006
Totally Distributed Motion Control of Sphere World Multi-agent Systems using Decentralized Navigation Functions · ICRA 2006
Knowledge, reasoning and agents › Multi-agent systems › multi-agent control
distributed motion control
0.112006
Totally Distributed Motion Control of Sphere World Multi-agent Systems using Decentralized Navigation Functions · ICRA 2006
Knowledge, reasoning and agents › Multi-agent systems
large-scale multi-agent systems
0.012006
Totally Distributed Motion Control of Sphere World Multi-agent Systems using Decentralized Navigation Functions · ICRA 2006

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

lyapunov stability for hybrid systems · 0.1
YearPublicationVenuePosition
2006 Totally Distributed Motion Control of Sphere World Multi-agent Systems using Decentralized Navigation Functions
abstract
A distributed feedback control architecture that guarantees collision avoidance and destination convergence for multiple sphere world holonomic agents is presented. The well established tool of decentralized navigation functions is redefined to cope with the communication restrictions of the system. Each agent plans its actions without knowing the destinations of the others and the positions of those agents lying outside its sensing neighborhood. The stability properties of the closed loop system are checked via Lyapunov stability techniques for hybrid systems. The collision avoidance and goal convergence properties are verified through simulations. The key advantage of the proposed algorithm with respect to the previous ones is the significant decrease of computational load and its applicability to large scale groups
Dimos V. Dimarogonas, Kostas J. Kyriakopoulos, Dimitris Theodorakatos
ICRA3