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S. Crinier

dblp:56/617 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2003
—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
Robot manipulation · 50% Motion planning and robot control · 50%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.012003
Vision and tactile sensing for real world tasks · ICRA 2003
Robotics › Motion planning and robot control › robot control › sensor-based control › visual servoing
robust visual servoing
0.012003
Vision and tactile sensing for real world tasks · ICRA 2003
Robotics › Robot manipulation › tactile sensing › tactile sensing for manipulation
tactile-based grasping
0.012003
Vision and tactile sensing for real world tasks · ICRA 2003
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.012003
Vision and tactile sensing for real world tasks · ICRA 2003

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

tactile feedback · 0.0
YearPublicationVenuePosition
2003 Vision and tactile sensing for real world tasks
abstract
Robotic fetch-and-carry tasks are commonly facilitated to demonstrate a number of research directions such as navigation, mobile manipulation, systems integration, etc. As a part of an integrated system in terms of a service robot framework, this paper describes a set of methods for real-world object manipulation tasks. We concentrate here on two particular parts of a manipulation sequence: i) robust visual servoing, and ii) grasping strategies. In terms of visual servoing we discuss the handling of singularities during a manipulation sequence. For grasping, we present a biologically motivated strategy using tactile feedback.
Danica Kragic, S. Crinier, Dietrich Brunn, Henrik I. Christensen
ICRA2