Search results for " robot"
showing 10 items of 408 documents
Design and validation of a neuroprosthesis for the treatment of upper limb tremor.
2013
Pathological tremor is the most prevalent movement disorder. In spite of the existence of various treatments for it, tremor poses a functional problem to a large proportion of patients. This paper presents the design and implementation of a novel neuroprosthesis for tremor management. The paper starts by reviewing a series of design criteria that were established after analyzing users needs and the expected functionality of the system. Then, it summarizes the design of the neuroprosthesis, which was built to meet the criteria defined previously. Experimental results with a representative group of 12 patients show that the neuroprosthesis provided significant (p <; 0.001) and systematic trem…
Robotic Radical Hysterectomy After Concomitant Chemoradiation in Locally Advanced Cervical Cancer: A Prospective Phase II Study
2016
Study Objective To assess the feasibility of total robotic radical surgery (TRRS) in patients with locally advanced cervical cancer (LACC) who receive chemoradiation therapy (CT/RT). Design A prospective (preplanned) study of a nonrandomized controlled trial (Canadian Task Force classification level 2). Setting Catholic University of the Sacred Hearth, Rome, Italy. Patients Between September 2013 and January 2016, a total of 40 patients with LACC (Fédération Internationale de Gynécologie et d'Obstétrique stage IB2–III) were enrolled in the study. Interventions Robotic radical hysterectomy (RRH) plus pelvic and/or aortic lymphadenectomy was attempted within 6 weeks after CT/RT. The feasibili…
Robotic Total Mesometrial Resection versus Laparoscopic Total Mesometrial Resection in Early Cervical Cancer: A Case-Control Study
2016
Abstract Study Objective To report our experience with robotic total mesometrial resection (R-TMMR) comparing perioperative results with a series of laparoscopic total mesometrial resections (L-TMMRs). Design Multicenter retrospective case-control study (Canadian Task Force classification II-2). Setting Catholic University of the Sacred Heart of Rome (Italy) and Campobasso (Italy). Patients From July 2013 to August 2015 all cervical cancer patients with preoperative FIGO stage IA2 to IB1 were assessed at preoperative magnetic resonance imaging scan and clinically confirmed by investigation under anesthesia, complying strictly with the FIGO criteria. Surgical and postsurgical data of the TMM…
Minimally Invasive Pelvic Exenteration for Gynecologic Malignancies: A Multi-Institutional Case Series and Review of the Literature.
2019
ABSTRACT Study Objective To assess the feasibility and efficacy of minimally invasive pelvic exenteration (MIPE) in a multi-institutional Italian case series of women with gynecologic cancer and a review of the literature. Design Retrospective cohort study (Canadian Task Force classification II-2). Setting Three Italian university/teaching hospitals: “Agostino Gemelli” Foundation University Hospital in Rome, "ARNAS Civico Di Cristina Benfratelli” Hospital in Palermo, and “Maggiore della Carita” Hospital in Novara. Patients We reviewed all consecutive cases with gynecologic malignancies in this multi-institutional setting recorded between March 2014 and June 2017. Women with primary or centr…
Real-time clothoid approximation by Rational Bezier curves
2008
This paper presents a novel technique for implementing Clothoidal real-time paths for mobile robots. As first step, rational Bezier curves are obtained as approximation of the Fresnel integrals. By rescaling, rotating and translating the previously computed RBC, an on-line Clothoidal path is obtained. In this process, coefficients, weights and control points are kept invariant. This on-line approach guarantees that an RBC has the same behavior as the original Clothoid using a low curve order. The resulting Clothoidal path allows any two arbitrary poses to be joined in a plane. RBCs working as Clothoids are also used to search for the shortest bounded-curvature path with a significant comput…
Modeling the insect mushroom bodies: application to a delayed match-to-sample task.
2013
Despite their small brains, insects show advanced capabilities in learning and task solving. Flies, honeybees and ants are becoming a reference point in neuroscience and a main source of inspiration for autonomous robot design issues and control algorithms. In particular, honeybees demonstrate to be able to autonomously abstract complex associations and apply them in tasks involving different sensory modalities within the insect brain. Mushroom Bodies (MBs) are worthy of primary attention for understanding memory and learning functions in insects. In fact, even if their main role regards olfactory conditioning, they are involved in many behavioral achievements and learning capabilities, as …
A Segmentation System for Soccer Robot Based on Neural Networks
2000
An innovative technique for segmentation of color images is proposed. The technique implements an approach based on thresholding of the hue histogram and a feed-forward neural network that learns to recognize the hue ranges of meaningful objects. A new function for detecting valleys of the histogram has been devised and tested. A novel blurring algorithm for noise reduction that works effectively when used over hue image has been employed. The reported experimental results show that the technique is reliable and robust even in presence of changing environmental conditions. Extended experimentation has been carried on the framework of the Robot Soccer World Cup Initiative (RoboCup).
State classification for autonomous gas sample taking using deep convolutional neural networks
2017
Despite recent rapid advances and successful large-scale application of deep Convolutional Neural Networks (CNNs) using image, video, sound, text and time-series data, its adoption within the oil and gas industry in particular have been sparse. In this paper, we initially present an overview of opportunities for deep CNN methods within oil and gas industry, followed by details on a novel development where deep CNN have been used for state classification of autonomous gas sample taking procedure utilizing an industrial robot. The experimental results — using a deep CNN containing six layers — show accuracy levels exceeding 99 %. In addition, the advantages of using parallel computing with GP…
Pose classification using support vector machines
2000
In this work a software architecture is presented for the automatic recognition of human arm poses. Our research has been carried on in the robotics framework. A mobile robot that has to find its path to the goal in a partially structured environment can be trained by a human operator to follow particular routes in order to perform its task quickly. The system is able to recognize and classify some different poses of the operator's arms as direction commands like "turn-left", "turn-right", "go-straight", and so on. A binary image of the operator silhouette is obtained from the gray-level input. Next, a slice centered on the silhouette itself is processed in order to compute the eigenvalues …
A Neural Solution for a Mobile Robot Navigation into Unknown Indoor Environments Using Visual Landmarks
1998
In this paper we present a neural solution for a mobile robot navigation into unknown indoor environments by using landmarks. Robot navigation task is implemented by two groups of processes based on MLP neural networks classifiers: a Low Level Vision System performs obstacle avoidance and corridor following, while an High Level Vision System extracts landmarks contents and performs goal directed navigation. A path-planner manages the two navigation systems and interacts with the robot hardware. The proposed solution is very strong and flexible and can be used to drive a mobile robot in real indoor environments. In the paper experimental results are also reported.