Demo Data from VLDB 2026 / reviewers in the wild / expert
Andrew Rogers
dblp:166/3597
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-7634-2977ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, 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 |
Robot navigation and mapping · 33% Multi-agent systems · 33% Motion planning and robot control · 33% | |
| Computer networks
1 paper |
Internet of things and sensor networks · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control › motion control
closed-loop motion control |
0.6 | 1 | 2022 | Closed-Loop Motion Control of Robotic Swarms - A Tether-Based Strategy · IEEE Trans. Robotics 2022 |
Knowledge, reasoning and agents › Multi-agent systems › swarm robotics
swarm control |
0.6 | 1 | 2022 | Closed-Loop Motion Control of Robotic Swarms - A Tether-Based Strategy · IEEE Trans. Robotics 2022 |
Internet of things and sensor networks
mobile sensor networks |
0.2 | 1 | 2022 | Closed-Loop Motion Control of Robotic Swarms - A Tether-Based Strategy · IEEE Trans. Robotics 2022 |
Methods — techniques the papers use, named apart from their topics
wireless tether · 1.1closed-loop control · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Closed-Loop Motion Control of Robotic Swarms - A Tether-Based StrategyabstractSwarm robots can achieve effective task execution via closed-loop motion control. However, such a goal can only be realized through accurate localization of the swarm. Past approaches have focused on addressing this issue using external sensors, static sensor networks, or through active localization—requirements that may restrict the motion of the swarm or may not be achievable in practice. We present a tether-based strategy that achieves closed-loop swarm-motion control by using a secondary team of mobile sensors. These sensors form a wireless tether that allows the swarm to indirectly sense a home base or a landmark, and to compensate for the accumulated motion errors via a closed-loop control strategy. The proposed strategy is the first to use a tether of mobile sensors that can dynamically reshape and reconnect to various points in the environment to achieve closed-loop motion control. The novelty of the strategy is in its ability to adapt to any swarm motion considered, and to be applied to swarms with limited sensing capabilities and knowledge of their environment. The performance of the proposed strategy was validated through extensive experiments. Kasra Eshaghi, Andrew Rogers, Goldie Nejat, Beno Benhabib |
IEEE Trans. Robotics | 2 |