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Jeri Briscoe

dblp:20/824 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
field robotics
0.112005
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
0.112005
Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005
Robotics › Robot manipulation
robot design
0.012005
Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005
Mathematical optimization › multi-objective optimization
evolutionary algorithm
0.012005
Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot · ICRA 2005
Mathematical optimization › evolutionary computation
genetic algorithm
0.012005
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
YearPublicationVenuePosition
2005 Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot
abstract
Using 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
ICRA2