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R. Di Leonardo

dblp:81/8432 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1986
—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 · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
tactile sensing
0.011986
Geometrical optimization criteria for the design of tactile sensing patterns · ICRA 1986
Robotics › Robot manipulation › tactile sensing
tactile sensor design
0.011986
Geometrical optimization criteria for the design of tactile sensing patterns · ICRA 1986

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

space-variant sensing · 0.0pattern recognition · 0.0multifovea disposition · 0.0
YearPublicationVenuePosition
1986 Geometrical optimization criteria for the design of tactile sensing patterns
abstract
This paper addresses the problem of optimal geometrical design for tactile sensors. To this aim the particular case in which sensor-object contact information can be reduced to the form of a binary tactile image is considered. Possible criteria for the evaluation of space-invariant (orthogonal and hexagonal grids) and space-variant (retina-like and "multifovea") dispositions of sensing elements are discussed. Simulation studies are carried on to compare space-invariant configurations in terms of rate of success in pattern recognition, and to evaluate the efficiency of the multifovea disposition in the calculation of position and orientation of sample objects. Finally, results obtained by applying different pattern recognition algorithms to the analysis of pseudovisual images provided by a real sensorized static platform are presented.
Paolo Dario, Massimo Bergamasco, Antonino S. Fiorillo, R. Di Leonardo
ICRA4