EDBT 2026 Demo / reviewers in the wild / expert
Roberto Armellin
dblp:150/1683
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0002-3516-6428ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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 |
Motion planning and robot control · 100% | |
| Computer networks
1 paper |
Cellular and mobile networks · 77% Vehicular, aerial and satellite networks · 12% Physical-layer communications · 12% |
Topics — the 8 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
control lyapunov function |
0.9 | 1 | 2025 | Reinforcement Learning Enhanced LQR and Control Lyapunov Functions for Spacecraft Proximity Operations · IEEE Trans. Robotics 2025 |
Robotics › Motion planning and robot control › robot control › optimal control
linear quadratic regulator |
0.9 | 1 | 2025 | Reinforcement Learning Enhanced LQR and Control Lyapunov Functions for Spacecraft Proximity Operations · IEEE Trans. Robotics 2025 |
Robotics › Motion planning and robot control
robot control |
0.9 | 1 | 2025 | Reinforcement Learning Enhanced LQR and Control Lyapunov Functions for Spacecraft Proximity Operations · IEEE Trans. Robotics 2025 |
Cellular and mobile networks
6g |
0.8 | 1 | 2024 | On the Use of Mega Constellation Services in Space: Integrating LEO Platforms Into 6G Non-Terrestrial Networks · IEEE J. Sel. Areas Commun. 2024 |
Cellular and mobile networks › 6g
non-terrestrial networks |
0.8 | 1 | 2024 | On the Use of Mega Constellation Services in Space: Integrating LEO Platforms Into 6G Non-Terrestrial Networks · IEEE J. Sel. Areas Commun. 2024 |
Robotics › Motion planning and robot control › robot control
learning control |
0.3 | 1 | 2025 | Reinforcement Learning Enhanced LQR and Control Lyapunov Functions for Spacecraft Proximity Operations · IEEE Trans. Robotics 2025 |
Physical-layer communications › modulation
adaptive modulation and coding |
0.2 | 1 | 2024 | On the Use of Mega Constellation Services in Space: Integrating LEO Platforms Into 6G Non-Terrestrial Networks · IEEE J. Sel. Areas Commun. 2024 |
Vehicular, aerial and satellite networks
satellite communication |
0.2 | 1 | 2024 | On the Use of Mega Constellation Services in Space: Integrating LEO Platforms Into 6G Non-Terrestrial Networks · IEEE J. Sel. Areas Commun. 2024 |
Methods — techniques the papers use, named apart from their topics
reinforcement learning · 0.9control lyapunov function · 0.9LQR · 0.9monte carlo simulation · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Reinforcement Learning Enhanced LQR and Control Lyapunov Functions for Spacecraft Proximity Operations
Harry Holt, Roberto Armellin |
IEEE Trans. Robotics | 2 |
| 2024 | On the Use of Mega Constellation Services in Space: Integrating LEO Platforms Into 6G Non-Terrestrial NetworksabstractThis paper presents a framework for integrating Low-Earth Orbit (LEO) platforms with Non-Terrestrial Networks (NTNs) in the emerging 6G communication landscape. Our work applies the Mega-Constellation Services in Space (MCSS) paradigm, leveraging LEO mega-constellations’ expansive coverage and capacity, designed initially for terrestrial devices, to serve platforms in lower LEO orbits. Results show that this approach overcomes the limitation of sporadic and time-bound satellite communication links, a challenge not fully resolved by available Ground Station Networks and Data Relay Systems. We contribute three key elements: (i) a detailed MCSS evaluation framework employing Monte Carlo simulations to assess space user links and distributions; (ii) a novel Space User Terminal (SUT) design optimized for MCSS, using different configurations and 5G New Radio Adaptive Coding and Modulation; (iii) extensive results demonstrating MCSS’s substantial improvement over existing Ground Station Networks and Data Relay Systems, motivating its role in the upcoming 6G NTNs. The space terminal, incorporating a multi-system, multi-orbit, and software-defined architecture, can handle Terabit-scale daily data volumes and minute-scale latencies. It offers a compact, power-efficient solution for properly integrating LEO platforms as space internet nodes. Gabriel Maiolini Capez, Mauricio A. Cáceres, Roberto Armellin, Christopher P. Bridges, Juan A. Fraire, Stefan Frey, Roberto Garello |
IEEE J. Sel. Areas Commun. | 3 |