A Dynamic Manipulation Strategy for an Intervention Autonomous Underwater Vehicle

This paper presents the modelling and the control architecture of an Autonomous Underwater Vehicle for Intervention (I-AUV). Autonomous underwater manipulation with free-floating base is still an open topic of research, far from reaching an industrial product. Dynamic manipulation tasks, where relevant vehicle velocities are required during manipulation, over an additional challenge. In this paper, the accurate modelling of an I-AUV is described, not neglecting the interaction with the fluid. A grasp planning strategy is proposed and integrated in the control of the whole system. The performances of the I-AUV have been analysed by means of simulations of a dynamic manipulation task

Modelling and Control of an Autonomous Underwater Vehicle for Mobile Manipulation

In the last few years the development of the Autonomous Underwater Vehicles (AUVs) has had a greater importance because of their fundamental applications in the military field, in underwater explorations (e.g. archaeological field) and in the industrial field (e.g. for Oil&Gas). More specifically, in the evolution of the AUVs the following topics hold an important position, which are still characterized by many open problems: the dynamic performances and the control of the single vehicle, the mobile tele-manipulation of a single vehicle and the cooperation among vehicles (whether including the manipulation operations or not) [1] [2] [3] [5]. In this work the authors describe the multibody modelling and the control architecture of an AUV specifically thought for the mobile underwater manipulation, usually called I-AUV (AUV for Intervention). The performances of such an AUV will have to meet strict planning and control specifications, both as regards the vehicle itself and as for the manipulation phase

Epilepsy in Neurodegenerative Dementias: A Clinical, Epidemiological, and EEG Study

BACKGROUND: Seizures are common in patients with dementia but precise epidemiologic data of epilepsy in neurodegenerative dementia is lacking. OBJECTIVE: The first aim of the study was to investigate prevalence and clinical characteristics of epilepsy in a large cohort of patients with neurodegenerative dementias. Subsequently, we explored clinical, neuropsychological, and quantitative electroencephalogram (qEEG) data of Alzheimer's disease (AD) patients with epilepsy (AD-EPI) as compared to AD patients without epilepsy (AD-CTR). METHODS: We retrospectively evaluated consecutive patients with a diagnosis of a neurodegenerative dementia and a clinically diagnosed epilepsy that required antiepileptic drugs (AED). All patients underwent baseline comprehensive neuropsychological assessment. A follow-up of at least one year was requested to confirm the dementia diagnosis. In AD patients, qEEG power band analysis was performed. AD-CTR and AD-EPI patients were matched for age, Mini-Mental State Examination score, and gender. RESULTS: Thirty-eight out of 2,054 neurodegenerative dementia patients had epilepsy requiring AED. The prevalence of epilepsy was 1.82% for AD, 1.28% for the behavioral variant of frontotemporal dementia (bvFTD), 2.47% for dementia with Lewy bodies (DLB), and 12% for primary progressive aphasia. Epilepsy were more drug-responsive in AD than in non-AD dementias. Finally, no significant differences were found in neuropsychological and qEEG data between AD-EPI and AD-CTR patients. CONCLUSION: In our cohort, AD, FTD, and DLB dementias have similar prevalence of epilepsy, even if AD patients were more responsive to AED. Moreover, AD-EPI patients did not have significant clinical, neuropsychological qEEG differences compared with AD-CTR patients

Prolonged higher dose methylprednisolone vs. conventional dexamethasone in COVID-19 pneumonia: a randomised controlled trial (MEDEAS)

Dysregulated systemic inflammation is the primary driver of mortality in severe COVID-19 pneumonia. Current guidelines favor a 7-10-day course of any glucocorticoid equivalent to dexamethasone 6 mg·day-1. A comparative RCT with a higher dose and a longer duration of intervention was lacking

A free floating manipulation strategy for Autonomous Underwater Vehicles

Free floating autonomous underwater manipulation is still an open research topic; an important challenge is offered by free floating manipulation, where the vehicle maintains relevant velocities during manipulation tasks. This paper focuses on the modelling and the control of an Autonomous Underwater Vehicle for Intervention (I-AUV). To this aim, an accurate model of the I-AUV has been implemented, including the interaction with the fluid. Then, a control architecture for the whole system is proposed, with particular attention on a suitable grasp planning strategy. Finally, a free floating manipulation task has been simulated to analyse in detail the performances of the I-AUV control system

Semantic Monocular Surgical SLAM: Intra-Operative 3D Reconstruction and Pre-Operative Registration in Dynamic Environments

In recent years, the feasibility of autonomy in the field of Robotic-Assisted Minimally Invasive Surgery (RAMIS) has been investigated. One of the most important requirements for such a system is the capability of reconstructing the patient's 3D anatomy in real-time and registering it with pre-operative data. This is a crucial step for surgical guidance and augmented reality applications. A common solution is to use Simultaneous Localization and Mapping (SLAM) which plays an important role in the field of computer vision and robotics. Conventional SLAM algorithms assume to operate in a static environment, which is clearly in contrast with the non-rigid and ever-changing nature of the surgical scene. In this paper, we propose a novel approach to monocular SLAM, combining geometric and semantic segmentation based on prior intervention-specific knowledge to automatically isolate dynamic objects and increase the accuracy of 3D reconstruction. Then, we register the sparse reconstructed point cloud with the preoperative anatomical model. The proposed approach is tested on an anatomically realistic phantom for partial nephrectomy with the da Vinci Research Kit (dVRK) endoscope. We compare our methodology with the state-of-the-art ORB-SLAM2 and perform an ablation study to assess the impact of semantic and geometric segmentation on the quality of reconstruction and registration