Demo Data from EDBT 2026 / reviewers in the wild / expert
Jeri Briscoe
dblp:20/824
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2005
—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 |
Legged, aerial and field robots · 87% Robot manipulation · 13% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
field robotics |
0.1 | 1 | 2005 | Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005 |
Robotics › Legged, aerial and field robots › field robotics › pipeline robotics
pipe-crawling robot |
0.1 | 1 | 2005 | Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005 |
Robotics › Robot manipulation
robot design |
0.0 | 1 | 2005 | Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005 |
Mathematical optimization › multi-objective optimization
evolutionary algorithm |
0.0 | 1 | 2005 | Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005 |
Mathematical optimization › evolutionary computation
genetic algorithm |
0.0 | 1 | 2005 | Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005 |
Methods — techniques the papers use, named apart from their topics
genetic algorithm · 0.1darwin2k simulation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection RobotabstractUsing the Darwin2k development software, a genetic algorithm (GA) was used to design and optimize a pipe-crawling robot for parameters such as mass, power consumption, and joint extension to further the research of the Miniature Inspection Systems Technology (MIST) team. In an attempt to improve on existing designs, a new robot was developed, the piezo robot. The final proposed design uses piezoelectric expansion actuators to move the robot with a ‘ chimneying’ method employed by mountain climbers and greatly improves on previous designs in load bearing ability, pipe traversing specifications, and field usability. This research shows the advantages of GA assisted design in the field of robotics. Geoffrey A. Hollinger, Jeri Briscoe |
ICRA | 2 |