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K. Sarrigeorgidis

dblp:68/4048 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1998
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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
Motion planning and robot control · 91% Legged, aerial and field robots · 9%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control		 0.011998
Motion Control of the N.T.U.A. Robotic Snake on a Planar Surface · ICRA 1998
Robotics › Motion planning and robot control › robot control
stabilization		 0.011998
Motion Control of the N.T.U.A. Robotic Snake on a Planar Surface · ICRA 1998
Robotics › Motion planning and robot control › robot control
trajectory tracking		 0.011998
Motion Control of the N.T.U.A. Robotic Snake on a Planar Surface · ICRA 1998
Robotics › Legged, aerial and field robots › bio-inspired robot
snake robot		 0.011998
Motion Control of the N.T.U.A. Robotic Snake on a Planar Surface · ICRA 1998

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

kinematic model · 0.0flat systems · 0.0dynamic state feedback · 0.0
YearPublicationVenuePosition
1998 Motion Control of the N.T.U.A. Robotic Snake on a Planar Surface
abstract
We extend our previous work (1997, 1998) on steering a robotic snake and we now address the problems of (i) stabilization about an arbitrary configuration and (ii) tracking an arbitrary trajectory. For stabilization we apply three different algorithms for the kinematic model derived in the previous work. Comparisons of the three feedback stabilizing controls are made. Trajectory tracking is firstly addressed under the notion of flat systems. In a second approach we make use of a dynamic state feedback in order to achieve dynamic decoupling of our system.
K. Sarrigeorgidis, Kostas J. Kyriakopoulos
 ICRA1