Demo Data from EDBT 2026 / reviewers in the wild / expert
Michael D. Sankur
dblp:265/5190
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0001-5083-3287ORCID · reported
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 |
Robot navigation and mapping · 91% Multi-agent systems · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
localization |
0.2 | 1 | 2016 | Towards a hyperbolic acoustic one-way localization system for underwater swarm robotics · ICRA 2016 |
Robotics › Robot navigation and mapping
sound source localization |
0.2 | 1 | 2016 | Towards a hyperbolic acoustic one-way localization system for underwater swarm robotics · ICRA 2016 |
Robotics › Robot navigation and mapping › localization › GPS-denied localization
underwater localization |
0.2 | 1 | 2016 | Towards a hyperbolic acoustic one-way localization system for underwater swarm robotics · ICRA 2016 |
Knowledge, reasoning and agents › Multi-agent systems
swarm robotics |
0.1 | 1 | 2016 | Towards a hyperbolic acoustic one-way localization system for underwater swarm robotics · ICRA 2016 |
Methods — techniques the papers use, named apart from their topics
time difference of arrival · 0.2extended kalman filter · 0.2cross-correlation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Towards a hyperbolic acoustic one-way localization system for underwater swarm roboticsabstractA hyperbolic acoustic system for underwater robot self-localization is presented. Anchored transducers send acoustic signals which are observed by a receiver. The system is passive with one-way signal transmission. Time differences of arrival (TDOAs) between the emitted signals are estimated by the receiver via cross-correlation. These TDOAs are fed to an Extended Kalman Filter to estimate the global position of the receiver. We describe the complete signal processing chain as well as challenges in hardware and software design. Experimental results in air and water show the feasibility of the system. This paper demonstrates that acoustic one-way localization is possible with off-the-shelf hardware in experimental test tanks. Andreas Rene Geist, Axel Hackbarth, Edwin Kreuzer, Viktor Rausch, Michael D. Sankur, Eugen Solowjow |
ICRA | 5 |