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Fusing Dexterity and Perception for Soft Robot-Assisted Minimally Invasive Surgery: What We Learnt from STIFF-FLOP

Articolo
Data di Pubblicazione:
2021
Abstract:
In recent years we have seen tremendous progress in the development of robotic solutions for minimally invasive surgery (MIS). Indeed, a number of robot-assisted MIS systems have been developed to product level and are now well-established clinical tools; Intuitive Surgical’s very successful da Vinci Surgical System a prime example. The majority of these surgical systems are based on the traditional rigid-component robot design that was instrumental in the third industrial revolution—especially within the manufacturing sector. However, the use of this approach for surgical procedures on or around soft tissue has come under increasing criticism. The dangers of operating with a robot made from rigid components both near and within a patient are considerable. The EU project STIFF-FLOP, arguably the first large-scale research programme on soft robots for MIS, signalled the start of a concerted effort among researchers to investigate this area more comprehensively. While soft robots have many advantages over their rigid-component counterparts, among them high compliance and increased dexterity, they also bring their own specific challenges when interacting with the environment, such as the need to integrate sensors (which also need to be soft) that can determine the robot’s position and orientation (pose). In this study, the challenges of sensor integration are explored, while keeping the surgeon’s perspective at the forefront of ourdiscussion. The paper critically explores a range of methods, predominantly those developed during the EU project STIFF-FLOP, that facilitate the embedding of soft sensors into articulate soft robot structures using flexible, optics-based lightguides. We examine different optics-based approaches to pose perception in a minimally invasive surgery settings, and methods of integration are also discussed.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
soft robotics; soft pose sensing; sensor integration; robot-assisted minimally invasive surgery; EU project STIFF-FLOP
Elenco autori:
Dawood, Abu Bakar; Fras, Jan; Aljaber, Faisal; Mintz, Yoav; Arezzo, Alberto; Godaba, Hareesh; Althoefer, Kaspar
Autori di Ateneo:
AREZZO Alberto
Link alla scheda completa:
https://iris.unito.it/handle/2318/1794550
Pubblicato in:
APPLIED SCIENCES
Journal
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