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Francesco Visentin

dblp:43/10011 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2026
0000-0002-0879-7283ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author

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.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%
Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%
Artificial intelligence
1 paper
Robot navigation and mapping · 87% Legged, aerial and field robots · 13%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › bioimage informatics
bioimage analysis
1.012026
Image-based Morphological Characterization of Filamentous Biological Structures with Non-constant Curvature Shape Feature · Int. J. Comput. Vis. 2026
Geometric modeling and processing
shape analysis
1.012026
Image-based Morphological Characterization of Filamentous Biological Structures with Non-constant Curvature Shape Feature · Int. J. Comput. Vis. 2026
Robotics › Robot navigation and mapping › obstacle detection
dynamic obstacle detection
0.412019
Dynamic Obstacles Detection for Robotic Soil Explorations · ICRA 2019
Robotics › Robot navigation and mapping
obstacle detection
0.412019
Dynamic Obstacles Detection for Robotic Soil Explorations · ICRA 2019
Robotics › Legged, aerial and field robots
field robotics
0.112019
Dynamic Obstacles Detection for Robotic Soil Explorations · ICRA 2019

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

force/torque sensing · 0.4
YearPublicationVenuePosition
2026 Image-based Morphological Characterization of Filamentous Biological Structures with Non-constant Curvature Shape Feature
Francesco Visentin, Barbara Mazzolai, Emanuela Del Dottore
Int. J. Comput. Vis.2
2019 Dynamic Obstacles Detection for Robotic Soil Explorations
abstract
Nowadays, robots can navigate complex and dynamic environments such as air, water, and different terrain. However, moving into the underground, and especially into the soil, is still a challenge. Soil is a complex environment, and its exploration and monitoring is a crucial aspect in different engineering fields. Although some robotic solutions for mapping the soil are available, none of them can navigate into it. In this work, we propose a new solution for dynamic obstacles detection by embedding a 6-axis force torque sensor into a plant-inspired robot for soil exploration. We measured the forces acting on the apical part of the robot while it penetrates the soil by growing. We tested the system in different configurations, and at different depths. Results show that it is possible to identify the relative position of the obstacle before touching it with the robot. By using the proposed method as control feedback it is possible to move toward the development of novel robotic systems for navigating in complex and dynamic environments, such as the soil.
Francesco Visentin, Ali Sadeghi, Barbara Mazzolai
ICRA1