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Enis Ersü

dblp:05/4876 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 1987
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 2 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
2 papers
Motion planning and robot control · 67% Reinforcement learning · 25% Representation and self-supervised learning · 8%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot kinematics
forward kinematics
0.011984
A numerical solution of the general kinematic problem · ICRA 1984
Robotics › Motion planning and robot control › robot control
inverse kinematics
0.011984
A numerical solution of the general kinematic problem · ICRA 1984
Robotics › Motion planning and robot control › robot control › inverse kinematics
numerical inverse kinematics
0.011984
A numerical solution of the general kinematic problem · ICRA 1984
Robotics › Motion planning and robot control
robot kinematics
0.011984
A numerical solution of the general kinematic problem · ICRA 1984
Machine learning › Representation and self-supervised learning
associative memory
0.011987
Hierarchical Learning Control - An Approach with Neuron-Like Associative Memories · NIPS 1987

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

neuron-like associative memory · 0.0linearization · 0.0homogeneous transformation matrices · 0.0
YearPublicationVenuePosition
1987 Hierarchical Learning Control - An Approach with Neuron-Like Associative Memories
Enis Ersü, Henning Tolle
NIPS1
1984 A numerical solution of the general kinematic problem
abstract
The paper proposes a method for the solution of the general kinematic problem, i.e. the transformations between the joint coordinate and the cartesian robot coordinate system. Based on homogeneous transformation matrices the method solves the kinematic problem for a series of n (n >/=/< 6) one-degree-of-freedom joints either revolute or prismatic and with or without branching analytically. The inverse kinematic problem is handled numerically via linearization. The numerical solution is evaluated with respect to some constraints like joint workspace, velocities, energy, e.t.c. The numerical results and the computation time show the applicability of the method for real-time control systems.
Enis Ersü, D. Nungesser
ICRA1