Dimos V. Dimarogonas

18.7k citations
399 papers · 13.5k indexed · 7 hit papers · h-index 53

Dimos V. Dimarogonas

383 papers receiving 13.1k citations

Hit Papers

Dynamic Event-Triggered and Self-Tr...383200720262013201950010001.5k

Peers

Dimos V. Dimarogonas
Comparison fields: 5 of 109
  • Computer Networks and Communications 8.8k
  • Control and Systems Engineering 7.2k
  • Computational Theory and Mathematics 1.6k
  • Computer Vision and Pattern Recognition 1.7k
  • Software 273
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Yun Zhang China
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Countries citing papers authored by Dimos V. Dimarogonas

Since Specialization
Citations

This map shows the geographic impact of Dimos V. Dimarogonas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dimos V. Dimarogonas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dimos V. Dimarogonas more than expected).

Fields of papers citing papers by Dimos V. Dimarogonas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dimos V. Dimarogonas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dimos V. Dimarogonas. The network helps show where Dimos V. Dimarogonas may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Dimos V. Dimarogonas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dimos V. Dimarogonas Line = papers co-authored together Dimos V. Dimarogonas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20242
3 20241
4 202321
5 202317
6 20232
7 202211
8 202217
9 202026
10 20209
11 2020137
12
Hierarchical LTL-Task MDPs for Multi-Agent Coordination through Auctioning and Learning
201910
13 20199
14 201792
15 201732
16
The Advantages of Using Behavior Trees in Mult-Robot Systems
201615
17 201632
18
A Robust Control Approach for Underwater Vehicle Manipulator Systems in Interaction with Compliant Environments.
20162
19
Event-triggered control for discrete-time systemsbreakdown →
2010277
20
Distributed 3D Navigation and Collision Avoidance Nonholonomic Aircraft-like Vehicles
20092

About Dimos V. Dimarogonas

Dimos V. Dimarogonas is a scholar working on Computer Networks and Communications, Control and Systems Engineering and Computational Theory and Mathematics, having authored 399 papers that have together received 13.5k indexed citations. Recurring topics across this work include Distributed Control Multi-Agent Systems (201 papers), Formal Methods in Verification (80 papers), Robotic Path Planning Algorithms (77 papers), Advanced Control Systems Optimization (77 papers), Adaptive Control of Nonlinear Systems (62 papers), Neural Networks Stability and Synchronization (56 papers), Stability and Control of Uncertain Systems (50 papers) and Control and Dynamics of Mobile Robots (35 papers). The work is most often cited by research in Computer Networks and Communications (8.8k citations), Control and Systems Engineering (7.2k citations) and Computational Theory and Mathematics (1.6k citations). Dimos V. Dimarogonas has collaborated with scholars based in Sweden, Greece and United States. Frequent co-authors include Karl Henrik Johansson, Kostas J. Kyriakopoulos, Emilio Frazzoli, Georg S. Seyboth, Meng Guo, Lars Lindemann, Alina Eqtami, Christos K. Verginis, Ziyang Meng and Kazumune Hashimoto. Their work appears in journals such as IEEE Transactions on Automatic Control, Automatica and The International Journal of Robotics Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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