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H. Hoeve

dblp:126/4741 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1996
—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 · 88% Motion planning and robot control · 12%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › tactile sensing
slip detection
0.011996
Slip detection by tactile sensors: algorithms and experimental results · ICRA 1996
Robotics › Robot manipulation
tactile sensing
0.011996
Slip detection by tactile sensors: algorithms and experimental results · ICRA 1996
Robotics › Motion planning and robot control › robot dynamics › contact dynamics
contact force analysis
0.011996
Slip detection by tactile sensors: algorithms and experimental results · ICRA 1996
Robotics › Robot manipulation
grasping
0.011996
Slip detection by tactile sensors: algorithms and experimental results · ICRA 1996

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

center of force distribution analysis · 0.0FFT frequency analysis · 0.0
YearPublicationVenuePosition
1996 Slip detection by tactile sensors: algorithms and experimental results
abstract
Two techniques for slip detection with a rubber-based tactile matrix sensor are presented. The described results have been obtained within a common research activity between the Robotics and Automation Laboratory of the University of Bologna and the Control Laboratory of the Delft University of Technology. The first technique is based on a frequency analysis of the position of the center of force distribution. The main idea is that before a slip situation actually occurs, it is possible to detect a micro movement of the object due to the elasticity of the rubber. By implementing a FFT of the center of distribution and by testing the frequency components, the slip is identified before it practically occurs. The second approach is based on the principle that the normal forces measured by the tactile sensor fluctuate with a certain frequency during slip because of the rubber elasticity. This fluctuation is due to a 'catch and snap back' effect, which is present when an object is slipping over the sensor's surface. By testing the frequency domain of the normal force a slip condition can be detected. A comparison of the two approaches is presented and discussed on the basis of experimental results obtained in both laboratories.
E. G. M. Holweg, H. Hoeve, W. Jongkind, Lorenzo Marconi 0001, Claudio Melchiorri, Claudio Bonivento
ICRA2