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Georgios C. Gavridis

dblp:159/1855 · 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 · 56% Motion planning and robot control · 44%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots › aerial robots › aerial physical interaction
aerial manipulation
0.212015
Mechanical design, modelling and control of a novel aerial manipulator · ICRA 2015
Robotics › Legged, aerial and field robots
aerial robots
0.212015
Mechanical design, modelling and control of a novel aerial manipulator · ICRA 2015
Robotics › Motion planning and robot control › manipulator control
end-effector control
0.212015
Mechanical design, modelling and control of a novel aerial manipulator · ICRA 2015
Robotics › Motion planning and robot control › robot control › adaptive control
adaptive backstepping control
0.112015
Mechanical design, modelling and control of a novel aerial manipulator · ICRA 2015
Robotics › Motion planning and robot control
robot control
0.112015
Mechanical design, modelling and control of a novel aerial manipulator · ICRA 2015

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

kinematic modeling · 0.2dynamic modeling · 0.2adaptive backstepping · 0.2CAD · 0.2
YearPublicationVenuePosition
2015 Mechanical design, modelling and control of a novel aerial manipulator
abstract
In this paper a novel aerial manipulation system is proposed. The mechanical structure of the system, the number of thrusters and their geometry will be derived from technical optimization problems. The aforementioned problems are defined by taking into consideration the desired actuation forces and torques applied to the end-effector of the system. The framework of the proposed system is designed in a CAD Package in order to evaluate the system parameter values. Following this, the kinematic and dynamic models are developed and an adaptive backstepping controller is designed aiming to control the exact position and orientation of the end-effector in the Cartesian space. Finally, the performance of the system is demonstrated through a simulation study, where a manipulation task scenario is investigated.
Alexandros Nikou, Georgios C. Gavridis, Kostas J. Kyriakopoulos
ICRA2