Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Hyperplasia of alveolar neuroendocrine cells in rat lung carcinogenesis by silica with selective expression of proadrenomedullin-derived peptides and amidating enzymes

Pulmonary neuroendocrine (NE) cells are found as clusters called neuroepithelial bodies (NEBs) or as single cells scattered in the respiratory epithelium. They express a variety of bioactive peptides, and they are thought to be the origin of NE lung tumors. Proadrenomedullin N-terminal 20 peptide (PAMP) is a peptide derived from the same precursor as adrenomedullin (AM). AM and PAMP are C-terminally amidated during their processing by a well-characterized amidating enzyme, peptidylglycine alpha-amidating monooxygenase (PAM). We explored AM, PAMP, and PAM expression as markers for NE hyperplasia in three rodent species (Fischer 344 rats, Syrian golden hamsters, and A/J mice) after a single intratracheal instillation of crystalline silica (quartz), which was previously found to induce different reactions in the three species. Rats developed a marked silicosis, with alveolar and bronchiolar hyperplasia and formation of peripheral lung epithelial tumors. Mice developed a moderate degree of silicosis, but not epithelial hyperplasia or tumors. Hamsters showed dust-storage lesions, but not silicosis or tumors. NE cells were immunolabeled for calcitonin gene-related peptide (CGRP), AM, PAMP, and PAM in serial sections of each lung. The numbers of positive NEBs per lung area and positive cells per NEB were quantified. A marked hyperplastic reaction in the NEBs of silica treated rats occurred only in alveolar NEBs, but not in bronchiolar NEBs. From Month 11 onwards, there were marked differences in the number of alveolar NEBs per section and in the number of cells per alveolar NEB immunoreactive for CGRP. No hyperplastic NE cell reaction was observed in silica-treated mice and hamsters. Significant PAMP and PAM expression was seen only in rat hyperplastic alveolar and in bronchiolar NEBs from Month 11 onwards. In E18, rat fetal lung NEBs were found to be strongly positive for PAMP and PAM

Paving the way for culturally competent robots: a position paper

Cultural competence is a well known requirement for an effective healthcare, widely investigated in the nursing literature. We claim that personal assistive robots should likewise be culturally competent, aware of general cultural characteristics and of the different forms they take indifferent individuals, and sensitive to cultural differences while perceiving, reasoning, and acting. Drawing inspiration from existing guidelines for culturally competent healthcare and the state-of-the-art in culturally competent robotics, we identify the key robot capabilities which enable culturally competent behaviours and discuss methodologies for their development and evaluation

A Planner for Ambient Assisted Living: From High-Level Reasoning to Low-Level Robot Execution and Back

Robot ecologies are a growing paradigm in which one or several robotic systems are integrated into a smart environment. Robotic ecologies hold great promises for elderly assistance. Planning the activities of these systems, however, is not trivial, and requires consideration of issues like temporal and information dependencies among different parts of the ecology, exogenous actions, and multiple, dynamic goals. We describe a planner able to cope with the above challenges. We show in particular how this planner has been incorporated in closed-loop into a full robotic system that performs daily tasks in support of elderly people. The full robot ecology is deployed in a test apartment inside a real residential building, and it is currently undergoing an extensive user evaluation

Altered expression of adhesion molecules and epithelial-mesenchymal transition in silica-induced rat lung carcinogenesis

Loss of the epithelial phenotype and disruption of adhesion molecules is a hallmark in the epithelial-mesenchymal transition (EMT) reported in several types of cancer. Most of the studies about the relevance of adhesion and junction molecules in lung cancer have been performed using established tumors or in vitro models. The sequential molecular events leading to EMT during lung cancer progression are still not well understood. We have used a rat model for multistep lung carcinogenesis to study the status of adherens and tight junction proteins and mesenchymal markers during EMT. After silica-induced chronic inflammation, rats sequentially develop epithelial hyperplasia, preneoplastic lesions, and tumors such as adenocarcinomas and squamous cell carcinomas. In comparison with normal and hyperplastic bronchiolar epithelium and with hyperplastic alveolar type II cells, the expression levels of E-cadherin, alpha-catenin and beta-catenin were significantly reduced in adenomatoid preneoplastic lesions and in late tumors. The loss of E-cadherin in tumors was associated with its promoter hypermethylation. alpha- and beta-catenin dysregulation lead to cytoplasmic accumulation in some carcinomas. No nuclear beta-catenin localization was found at any stage of any preneoplastic or neoplastic lesion. Zonula occludens protein-1 was markedly decreased in 66% of adenocarcinomas and in 100% squamous cell carcinomas. The mesenchymal-associated proteins N-cadherin and vimentin were analyzed as markers for EMT. N-cadherin was de novo expressed in 32% of adenocarcinomas and 33% of squamous cell carcinomas. Vimentin-positive tumor cells were found in 35% of adenocarcinomas and 88% of squamous cell carcinomas. Mesenchymal markers were absent in precursor lesions, both hyperplastic and adenomatoid. The present results show that silica-induced rat lung carcinogenesis is a good model to study EMT in vivo, and also provide in vivo evidence suggesting that the changes in cell-cell adhesion molecules are an early event in lung carcinogenesis, while EMT occurs at a later stage

A cognitive robotic ecology approach to self-configuring and evolving AAL systems

Robotic ecologies are systems made out of several robotic devices, including mobile robots, wireless sensors and effectors embedded in everyday environments, where they cooperate to achieve complex tasks. This paper demonstrates how endowing robotic ecologies with information processing algorithms such as perception, learning, planning, and novelty detection can make these systems able to deliver modular, flexible, manageable and dependable Ambient Assisted Living (AAL) solutions. Specifically, we show how the integrated and self-organising cognitive solutions implemented within the EU project RUBICON (Robotic UBIquitous Cognitive Network) can reduce the need of costly pre-programming and maintenance of robotic ecologies. We illustrate how these solutions can be harnessed to (i) deliver a range of assistive services by coordinating the sensing & acting capabilities of heterogeneous devices, (ii) adapt and tune the overall behaviour of the ecology to the preferences and behaviour of its inhabitants, and also (iii) deal with novel events, due to the occurrence of new user's activities and changing user's habits

The RACE Project: Robustness by Autonomous Competence Enhancement

This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work