9 research outputs found
Design and development of a Soft Robotic instrument for manipulation in Minimally Invasive Surgery
This work describes the concept design, fabrication and experimental characterization of a novel soft robotic manipulator and discuss the feasibility of his utilization as a tool for grasping procedures in Minimally Invasive Surgery.
In particular it has been fabricated by casting silicone in molds, and with a cable-driven actuator mechanism.
The idea of this proposal is to study the feasibility to grip soft tissues by using soft instruments. The advantage are all related to the compliant intrinsically property of the elastomeric materials and exploiting it in a surgery tool would mean to be able to safely getting closer to soft tissues inside the unstructured workspace of abdominal cavity, without the risk of damaging blood vessels or organs during the manipulating procedures. This is equivalent to not worry too much about the control, simplifying the system without any sensors for the feedback, and only by exploiting the tension of the cables as element for real-time monitoring of deformation and pressure at the finger front-side. This assertion will be described and supported in the fourth chapters of this work by explaining the development of a mechanical model and experimental testing procedures to correlate the deformation and force exerted at the finger front-side with the tension of the cables.
As an introduction, in the first chapter an overview of the areas in which the work fits into will be done, in the second and in the third the concept design and fabrication process will be explained, in the fourth and fifth the experimental validation of the prototype will be described and the results with relative discuss will be listed. Finally in the sixth chapter, conclusions and future work will be drawn.
This work has been carried on at the Biorobotic Institute of Scuola Superiore Sant'Anna and at the Artificial Intelligence Laboratory of the University of Zurich
Smartphone-based food diagnostic technologies: A review
A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development of powerful lab-on-smartphone platforms for many important applications including medical diagnosis, environmental monitoring, and food safety analysis. This paper reviews the recent advancements and developments in the field of smartphone-based food diagnostic technologies, with an emphasis on custom modules to enhance smartphone sensing capabilities. These devices typically comprise multiple components such as detectors, sample processors, disposable chips, batteries and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. To date, researchers have demonstrated several promising approaches employing various sensing techniques and device configurations. We aim to provide a systematic classification according to the detection strategy, providing a critical discussion of strengths and weaknesses. We have also extended the analysis to the food scanning devices that are increasingly populating the Internet of Things (IoT) market, demonstrating how this field is indeed promising, as the research outputs are quickly capitalized on new start-up companies
'HighChest': An augmented freezer designed for smart food management and promotion of eco-efficient behaviour
This paper introduces HighChest, an innovative smart freezer designed to promote energy efficient behavior and the responsible use of food. Introducing a novel humanâmachine interface (HMI) design developed through assessment phases and a user involvement stage, HighChest is state of the art, featuring smart services that exploit embedded sensors and Internet of things functionalities, which enhance the local capabilities of the appliance. The industrial design thinking approach followed for the advanced HMI is intended to maximize the social impact of the food management service, enhancing both the user experience of the product and the userâs willingness to adopt eco- and energy-friendly behaviors. The sensor equipment realizes automatic recognition of food by learning from the users, as well as automatic localization inside the deposit space. Moreover, it provides monitoring of the applianceâs usage, avoiding temperature and humidity issues related to improper use. Experimental tests were conducted to evaluate the localization system, and the results showed 100% accuracy for weights greater or equal to 0.5 kg. Drifts due to the lid opening and prolonged usage time were also measured, to implement automatic reset corrections
Design and development of a soft robotic gripper for manipulation in minimally invasive surgery: a proof of concept
In-line industrial contaminants discrimination for the packaging sorting based on near-infrared reflectance spectroscopy: A proof of concept
The Industry 4.0 paradigm requires new technologies and methods not only to improve the profitability and the quality of the industrial production and products, but also new strategies to reduce the social and environmental impact of the production process. Many line manufacturing chains unbox and assembly components to create products, but create a large amount of waste that sometimes can't be recycled because of the exposure to contaminants. When it comes to the automotive industry, mineral oils may contaminate plastic packaging and cardboard boxes during manufacturing, making hard to recycle them. In this paper we propose a proof of concept of a packaging sorting system based on NIR spectroscopy, to automate sorting and get high quality outputs for the recycling of cardboard package boxes. Spectral datasets have been pre-processed and dimensionally reduced using PCA A SVM algorithm has been trained to distinguish between oil contaminated and non contaminated materials. Two NIR spectrometers with sensing range 640-1050 nm and 950-1650 nm have been used and evaluated, to select the proper sensor configuration. Eventually, the system classification accuracy was respectively up to the 98,68% and 98,64% using the 950-1650 nm and the 640-1050 nm spectrometers, demonstrating the opportunity to detect mineral oil contamination on boxes
Design and development of a soft robotic gripper for manipulation in minimally invasive surgery: a proof of concept
This paper proposes the use of soft materials for building robotic grippers for delicate and safe interactions. The work includes concept design, fabrication and first assessment and characterization of the proposed soft gripper, a novel robotic end-effector entirely made up of elastomeric material. As a significant case study, it has been specifically adapted as a grasping tool in Minimally Invasive Surgery, but its design has been conceived in such a way that its dimension can be easily scaled, to find application in all those fields where a safe interaction with fragile items or human co-workers is needed. Moreover, the process is flexible for including further features to enrich its behaviour