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John Thon

dblp:26/8367 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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 · 67% Autonomous driving · 33%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots › underwater robotics
underwater glider
0.112012
Miniature underwater glider: Design, modeling, and experimental results · ICRA 2012
Robotics › Legged, aerial and field robots
underwater robotics
0.112012
Miniature underwater glider: Design, modeling, and experimental results · ICRA 2012
Robotics › Autonomous driving
vehicle dynamics modeling
0.112012
Miniature underwater glider: Design, modeling, and experimental results · ICRA 2012
Computational science and engineering
computational fluid dynamics
0.012012
Miniature underwater glider: Design, modeling, and experimental results · ICRA 2012

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

dynamics modeling · 0.3computational fluid dynamics · 0.3
YearPublicationVenuePosition
2012 Miniature underwater glider: Design, modeling, and experimental results
abstract
The concept of gliding robotic fish combines gliding and fin-actuation mechanisms to realize energy-efficient locomotion and high maneuverability, and holds strong promise for mobile sensing in versatile aquatic environments. In this paper we present the modeling and design of a miniature fish-like glider, a key enabling component for gliding robotic fish. The full dynamics of the glider is first derived and then reduced to the sagittal plane, where the lift, drag, and pitch moment coefficients are obtained as linear or quadratic functions of the attack angle based on computational fluid dynamics (CFD) analysis. The model is used to design the glider by accommodating stringent constraints on dimensions yet meeting the desired specification on speed. A fully untethered prototype of underwater glider is developed, with a weight of 4 kg and length of 40 cm. With a net buoyancy of 20 g, it realizes a steady gliding speed of 20 cm/s. The volume and net buoyancy of this glider are less than 10% and 5%, respectively, of those of reported gliders in the literature, and its speed per unit net buoyancy is over 9 times of those other vehicles. Experimental results have shown that the model is able to capture well both the steady glide behavior under different control inputs, and the dynamics during transients.
Feitian Zhang, John Thon, Cody Thon, Xiaobo Tan 0001
ICRA2
2010 Analytical modeling and experimental studies of robotic fish turning
abstract
Turning is one of the most important maneuvers for biological and robotic fish. In our group's prior work, an analytical framework was proposed for modeling the steady turning of fish, given asymmetric, periodic body/tail movement or deformation. However, the approach was not illustrated with simulation or validated with experiments. The contributions of the current paper are three fold. First, an extension to the modeling framework is made with a more rigorous formulation of the force balance equation. Second, we have worked out two examples explicitly, one with an oscillating, rigid tail, and the other with a flexible tail having a uniform curvature, and compared their turning behaviors through numerical results. Third, for model validation purposes, a robotic fish prototype has been developed, with the tail shaft controlled precisely by a servo motor. For a rigid tail, experimental results have confirmed the model prediction that, for the tested range, the steady-state turning radius and turning period decrease with an increasing bias in the tail motion, and that the turning period drops with an increasing tail beat frequency. We have also found that, with a flexible fin attached to the tail shaft, the robot can achieve faster turning with a smaller radius than the case of a rigid fin, and modeling within the same framework is underway to understand this phenomenon.
Xiaobo Tan 0001, Michael Carpenter, John Thon, Freddie Alequin-Ramos
ICRA3