Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Lea Venturino

dblp:55/3896 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2005
—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
Reinforcement learning · 33% 3D vision · 33% Robot navigation and mapping · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
3d reconstruction
0.112005
Pre-Historical Cave Fruition through Robotic Inspection · ICRA 2005
Robotics › Robot navigation and mapping
map building
0.112005
Pre-Historical Cave Fruition through Robotic Inspection · ICRA 2005
Machine learning › Reinforcement learning › exploration › autonomous exploration
mobile robot exploration
0.112005
Pre-Historical Cave Fruition through Robotic Inspection · ICRA 2005

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

laser range finder · 0.1image-based 3d reconstruction · 0.1
YearPublicationVenuePosition
2005 Pre-Historical Cave Fruition through Robotic Inspection
abstract
This paper describes a technological solution for the remote fruition of an archaeological site, a cave hosting pre-historical heritage of relevant importance, using a properly equipped mobile robot. The goal is twofold: to increase the fruition of these precious paintings (both off-line and on-line with the robot moving in the cave) and to collect data (about the two-dimensional map of the complex cave and about the three-dimensional structure of the wall hosting the paints) that can be important to increase the understanding of the environment by the experts. The choice of the robot is suitable for this task before it does need a very light and minimal installation of mobile and reversible infrastructures: in fact in such an environment any intervention can cause significant damages to the archaeological site. The current modules are able to explore the cave to determine the most interesting zones (with a richer content of pre-historical wall paintings), to collect three-dimensional data (using a laser range finder) that allow the reconstruction of a planar map of the cave, the navigation between these relevant zones, the fine positioning with respect to the paintings and the reconstruction of a full three-dimensional model of the walls hosting the paints starting from a set of three images acquired from slightly different points of view.
Tommaso Gramegna, Lea Venturino, Massimo Ianigro, Giovanni Attolico, Arcangelo Distante
ICRA2