Frank Juliá Wise

dblp:353/5763 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0003-8534-758XORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 2 since 2021Systems, architecture and hardware · 2 · 2 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
2 papers
Robot manipulation · 95% Motion planning and robot control · 5%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › robot sensing › perception for manipulation
shape sensing
1.422024
A soft miniaturized continuum robot with 3D shape sensing via functionalized soft optical waveguides · ICRA 2024
A Soft Robot with Three Dimensional Shape Sensing and Contact Recognition Multi-Modal Sensing via Tunable Soft Optical Sensors · ICRA 2023
Robotics › Robot manipulation
soft robotics
1.422024
A soft miniaturized continuum robot with 3D shape sensing via functionalized soft optical waveguides · ICRA 2024
A Soft Robot with Three Dimensional Shape Sensing and Contact Recognition Multi-Modal Sensing via Tunable Soft Optical Sensors · ICRA 2023
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 › tactile sensing › contact sensing
contact detection
0.712023
A Soft Robot with Three Dimensional Shape Sensing and Contact Recognition Multi-Modal Sensing via Tunable Soft Optical Sensors · ICRA 2023
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
Robotics › Robot manipulation
grasping
0.212023
A Soft Robot with Three Dimensional Shape Sensing and Contact Recognition Multi-Modal Sensing via Tunable Soft Optical Sensors · ICRA 2023

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

optical waveguides · 0.8laser patterning · 0.8roughness tuning · 0.7laser micro-machining · 0.7
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
ICRA3
2023 A Soft Robot with Three Dimensional Shape Sensing and Contact Recognition Multi-Modal Sensing via Tunable Soft Optical Sensors
abstract
Soft optical sensing strategies are rapidly developing for soft robotic systems as a means to increase the controllability of soft compliant robots. In this paper, we present a roughness tuning strategy for the fabrication of soft optical sensors to achieve the dual functionality of shape sensing combined with contact recognition within a single multi-modal sensor. The molds used to fabricate the soft sensors are roughened via laser micromachining to achieve asymmetrical sensor responses when bent in opposite directions. We demonstrate the integration of these sensors into a fully soft robotic platform consisting of a multi-directional bending module with integrated 3D shape sensing and a gripper with tip position monitoring along with contact force recognition. We show the accuracy of our sensing strategy in validation experiments and a pick-and-place task is performed to demonstrate the robot's functionality.
Max McCandless, Frank Juliá Wise, Sheila Russo
ICRA2