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Johan Baeten

dblp:93/6712 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2002
—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 · 2 · 2 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 · 39% Robot manipulation · 30% Robot navigation and mapping · 30%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › active vision
eye-in-hand visual servoing
0.012002
Tool/Camera Configurations for Eye-in-Hand Hybrid Vision/Force Control · ICRA 2002
Robotics › Robot manipulation
grasping
0.012002
Tool/Camera Configurations for Eye-in-Hand Hybrid Vision/Force Control · ICRA 2002
Robotics › Motion planning and robot control › robot control › sensor-based control
vision-force control
0.012002
Tool/Camera Configurations for Eye-in-Hand Hybrid Vision/Force Control · ICRA 2002
Robotics › Motion planning and robot control › robot control architecture
task frame formalism
0.012002
Tool/Camera Configurations for Eye-in-Hand Hybrid Vision/Force Control · ICRA 2002

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

visual servoing · 0.0hybrid control · 0.0force control · 0.0
YearPublicationVenuePosition
2002 Tool/Camera Configurations for Eye-in-Hand Hybrid Vision/Force Control
abstract
In contrast to most hybrid vision/force research, this work uses eye-in-hand vision and force control. Mounting both sensors on the same end effector gives rise to new constraints, control issues and advantages, which are discussed in the paper. Four meaningful tool/camera configurations, being parallel or non-parallel endpoint closed-loop and fixed or variable endpoint open-loop are suggested. Several task examples (in 3D space), specified in the task frame formalism, illustrate the use of these four configurations. Experimental results for the fixed EOL configuration are presented.
Johan Baeten, Herman Bruyninckx, Joris De Schutter
ICRA1
2002 Shared control in hybrid vision/force robotic servoing using the task frame
abstract
Hybrid position/force control can be extended to incorporate visual servoing. Together with the task frame formalism (TFF), it forms the basis to easily model, implement and execute robotic tasks in an uncalibrated workspace, using traded, hybrid or shared vision/force control. This paper emphasizes shared control in which both vision and force simultaneously control a given task frame direction. Our work shows the usefulness and feasibility of a range of tasks using shared control. Moreover, it offers a framework based on the TFF to distinguish between different (and partly new) forms of shared control. Each basic form is illustrated by a robotic task with shared control in one direction. In addition, an extension to classify multi-dimensional shared control tasks is presented. As shown by the experimental results, the tasks at hand benefit from the shared control approach.
Johan Baeten, Herman Bruyninckx, Joris De Schutter
IROS1