Demo Data from SIGIR 2026 / reviewers in the wild / expert
R. Di Leonardo
dblp:81/8432
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
tactile sensing |
0.0 | 1 | 1986 | Geometrical optimization criteria for the design of tactile sensing patterns · ICRA 1986 |
Robotics › Robot manipulation › tactile sensing
tactile sensor design |
0.0 | 1 | 1986 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1986 | Geometrical optimization criteria for the design of tactile sensing patternsabstractThis 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 |
ICRA | 4 |