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Gerrit Kollegger

dblp:181/4157 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · unresolved

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
Motion planning and robot control · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot learning
movement primitives
0.212016
Movement primitives with multiple phase parameters · ICRA 2016
Robotics › Motion planning and robot control › robot control › motion control
speed control
0.212016
Movement primitives with multiple phase parameters · ICRA 2016
Robotics › Motion planning and robot control › trajectory planning
trajectory adaptation
0.212016
Movement primitives with multiple phase parameters · ICRA 2016

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

movement primitive learning · 0.2constraint satisfaction · 0.2
YearPublicationVenuePosition
2016 Movement primitives with multiple phase parameters
abstract
Movement primitives are concise movement representations that can be learned from human demonstrations, support generalization to novel situations and modulate the speed of execution of movements. The speed modulation mechanisms proposed so far are limited though, allowing only for uniform speed modulation or coupling changes in speed to local measurements of forces, torques or other quantities. Those approaches are not enough when dealing with general velocity constraints. We present a movement primitive formulation that can be used to non-uniformly adapt the speed of execution of a movement in order to satisfy a given constraint, while maintaining similarity in shape to the original trajectory. We present results using a 4-DoF robot arm in a minigolf setup.
Marco Ewerton, Guilherme Maeda, Gerhard Neumann, Viktor Kisner, Gerrit Kollegger, Josef Wiemeyer, Jan Peters 0001
ICRA5