Demo Data from EDBT 2026 / reviewers in the wild / expert
Mary E. Brooks
dblp:03/5421
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2004
—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 |
Robot manipulation · 77% Motion planning and robot control · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › robot design › robot mechanism design
metamorphic robot reconfiguration |
0.0 | 1 | 2004 | Enveloping Multi-pocket Obstacles with Hexagonal Metamorphic Robots · ICRA 2004 |
Robotics › Motion planning and robot control › multi-robot control
distributed reconfiguration |
0.0 | 1 | 2004 | Enveloping Multi-pocket Obstacles with Hexagonal Metamorphic Robots · ICRA 2004 |
Methods — techniques the papers use, named apart from their topics
substrate path planning · 0.0distributed reconfiguration schema · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | Enveloping Multi-pocket Obstacles with Hexagonal Metamorphic RobotsabstractThe problem addressed is reconfiguration planning for a metamorphic robotic system composed of any number of hexagonal robots when a single obstacle with multiple indentations or "pockets" is embedded in the goal environment. We extend our earlier work on filling a single pocket in an obstacle to the case where the obstacle surface may contain multiple pockets. The planning phase of our algorithm first determines whether the obstacle pockets provide sufficient clearance for module movement, i.e., whether the obstacle is "admissible". In this paper, we present algorithms that sequentially order individual pockets and order module placement inside each pocket. These algorithms ensure that every cell in each pocket is filled and that module deadlock and collision do not occur during reconfiguration. This paper also provides a complete overview of the planning stage that is executed prior to reconfiguration and presents a distributed reconfiguration schema for filling more than one obstacle pocket concurrently, followed by the envelopment of the entire obstacle. Lastly, we present examples of obstacles with multiple pockets that were successfully filled using our distributed reconfiguration simulator. Jennifer E. Walter, Mary E. Brooks, David Frank Little, Nancy M. Amato |
ICRA | 2 |