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Kamil Kuklinski

dblp:119/2604 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

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

Artificial intelligence and machine learning · 2Human-computer interaction and ubiquitous computing · 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.

Human-computer interaction and pervasive computing
2 papers
Human-robot interaction · 72% User interface design and tools · 28%

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

TopicWeightPapersLastEvidence papers
User interface design and tools › end-user programming
programming by demonstration
0.212016
A Comparison of Types of Robot Control for Programming by Demonstration · HRI 2016
Human-robot interaction
robot programming
0.212016
A Comparison of Types of Robot Control for Programming by Demonstration · HRI 2016
Human-robot interaction
learning from demonstration
0.212014
Intuitive error resolution strategies during robot demonstration · HRI 2014
Human-robot interaction
teleoperation
0.122016
A Comparison of Types of Robot Control for Programming by Demonstration · HRI 2016
Intuitive error resolution strategies during robot demonstration · HRI 2014
Human-robot interaction › teleoperation
robotic arm teleoperation
0.112014
Intuitive error resolution strategies during robot demonstration · HRI 2014

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

user study · 0.4teleoperation · 0.2kinesthetic guidance · 0.2
YearPublicationVenuePosition
2016 A Comparison of Types of Robot Control for Programming by Demonstration
abstract
Programming by Demonstration (PbD) is an efficient way for non-experts to teach new skills to a robot. PbD can be carried out in different ways, for instance, by kinesthetic guidance, teleoperation or by using external controls. In this paper, we compare these three ways of controlling a robot in terms of efficiency, effectiveness (success and error rate) and usability. In an industrial assembly scenario, 51 participants carried out peg-in-hole tasks using one of the three control modalities. The results show that kinesthetic guidance produces the best results. In order to test whether the problems during teleoperation are due to the fact that users cannot, like in kinesthetic guidance, switch between control points using traditional teleoperation devices, we designed a new device that allows users to switch between controls for large and small movements. A user study with 15 participants shows that the novel teleoperation device yields almost as good results as kinesthetic guidance.
Kerstin Fischer, Franziska Kirstein, Lars Christian Jensen, Norbert Krüger, Kamil Kuklinski, Maria Vanessa aus der Wieschen, Thiusius Rajeeth Savarimuthu
HRI5
2014 Intuitive error resolution strategies during robot demonstration
abstract
While robot learning from demonstration comes with great benefits [5], the intuitive interaction between naïve users and robots also poses challenges. For instance, users need to be prevented from causing damage and to be enabled to recover from errors. We studied the error resolution strategies of 28 lay users performing simple assembly tasks via teleoperation of a robotic arm in order to gain insight into the strategies users take. The two most common problems are too much pressure and singularity. Even though users were provided with instructions on how to undo singularity in an instruction video, they did not always recover successfully. In contrast, too much pressure, if noticed, was resolved mostly correctly by lifting the peg or by letting it drop into the hole rather than inserting it. Finally, users were quite clueless about how to resolve self-collision and over-rotation.
Maria Vanessa aus der Wieschen, Kerstin Fischer, Kamil Kuklinski
HRI3