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Viola Del Bono

dblp:383/4676 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · unresolved

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

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

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 · 91% Motion planning and robot control · 9%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
continuum robot
0.812024
A soft miniaturized continuum robot with 3D shape sensing via functionalized soft optical waveguides · ICRA 2024
Robotics › Robot manipulation › robot sensing › perception for manipulation
shape sensing
0.812024
A soft miniaturized continuum robot with 3D shape sensing via functionalized soft optical waveguides · ICRA 2024
Robotics › Robot manipulation
soft robotics
0.812024
A soft miniaturized continuum robot with 3D shape sensing via functionalized soft optical waveguides · ICRA 2024
Robotics › Motion planning and robot control › robot control › trajectory tracking
tip position tracking
0.212024
A soft miniaturized continuum robot with 3D shape sensing via functionalized soft optical waveguides · ICRA 2024

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

optical waveguides · 0.8laser patterning · 0.8
YearPublicationVenuePosition
2024 A soft miniaturized continuum robot with 3D shape sensing via functionalized soft optical waveguides
abstract
In this paper, we present a fully soft miniaturized continuum robot that integrates 3D optical shape sensing through functionalized tubing used as soft optical waveguides. The sensor is fabricated by laser patterning an off-the-shelf medical tubing, allowing for bidirectional responses to large curvatures in two bending directions, enabling 3D shape sensing and tip tracking of the continuum robot. The robot is able to bend and sense its own shape up to a curvature of 44.7 m-1, corresponding to a bending angle of 102°, having high-accuracy tracking capabilities, resulting in an average tracking error of 3.08 mm, that is 7.7 % of the robot length. The robot’s functionality was shown in validation experiments, including a real-time shape prediction through a graphical user interface.
Viola Del Bono, Max McCandless, Frank Juliá Wise, Sheila Russo
ICRA1