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M. Frenger

dblp:164/8215 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 · 50% Robot manipulation · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › robot design
bio-inspired robot design
0.212015
An alligator inspired modular robot · ICRA 2015
Robotics › Legged, aerial and field robots › underwater robotics
swimming robot
0.212015
An alligator inspired modular robot · ICRA 2015

Methods — techniques the papers use, named apart from their topics

simulation · 0.2hydrodynamic modeling · 0.2
YearPublicationVenuePosition
2015 An alligator inspired modular robot
abstract
Due to challenges, such as information collection in huge water, propulsion at different scales and manipulation in extreme fluid environments, wide application of unmanned underwater vehicles (UUVs) is limited. In this paper, an alligator modular robot, composed by 14 small robots, was inspired from the locomotion and morphologies of alligators and microorganisms. With the undulatory body and beating legs, the assembled large robot was able to maintain fast and maneuverable swimming for tasks executions at large Reynolds number. With a biologically optimized body aspect ratio (3.47), small modular robots achieved effective propulsion in viscous fluid. Facilitated by a dissembling system, small robots were automatically released from the large robot frame and swam around with independent actuation systems. Hydrodynamic model for the large and small robot were formulated, based on which the propulsion for the modular robot in large and low Reynolds numbers (Res) were simulated. Experiments were conducted to compare with the simulation results to further validate the proposed modular robot design.
M. Frenger, William R. Hamel
ICRA2