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Federico Campisano

dblp:201/5670 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, 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.

Artificial intelligence
1 paper
Robot manipulation · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › soft robotics
soft robotic skin
0.312017
Towards a soft robotic skin for autonomous tissue palpation · ICRA 2017
Medical and health informatics
surgical robotics
0.112017
Towards a soft robotic skin for autonomous tissue palpation · ICRA 2017

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

tactile element calibration · 0.6soft suction anchoring · 0.6
YearPublicationVenuePosition
2017 Towards a soft robotic skin for autonomous tissue palpation
abstract
Manual palpation is commonly used to localize tumors and other features buried deep inside organs during open surgery. This approach is not feasible in minimally invasive or robotic surgery, as the contact with the tissue is mediated by instruments. To address this problem, we propose a soft robotic skin (SRS) that can be deployed from a small incision and create a stiffness map in a single step. Such a skin is composed of a matrix of soft robotic tactile elements (SRTEs), each one able to expand and record the tissue response during expansion. In this paper, we firstly prove the feasibility of palpation using a single SRTE. Then, we present and test a soft-suction based anchoring mechanism able to keep the SRS in the desired position in contact with the tissue, allowing surgeons to palpate different sides of the organ. Finally, we detail a calibration method for the SRTE, and assess the feasibility of identifying lumps buried inside a soft tissue phantom, and then inside a chicken liver during an ex-vivo trial. Experimental results show that the SRTE was able to differentiate simulated lumps (up to 3.25 mm deep) from healthy tissue in both the phantom and the ex-vivo trials. These results, added to the ability of the suction gripper to compensate for the expansion forces of each SRTE, are paving the way for soft robotic autonomous tools that can be used for intraoperative mapping of tissue cancers.
Federico Campisano, Selim Ozel, Anand Ramakrishnan, Anany Dwivedi, Nikolaos Gkotsis, Cagdas D. Onal, Pietro Valdastri
ICRA1