A neural network approach to human posture classification and fall detection using RGB-D camera

In this paper, we describe a human posture classification and a falling detector module suitable for smart homes and assisted living solutions. The system uses a neural network that processes the human joints produced by a skeleton tracker using the depth streams of an RGB-D sensor. The neural network is able to recognize standing, sitting and lying postures. Using only the depth maps from the sensor, the system can work in poor light conditions and guarantees the privacy of the person. The neural network is trained with a dataset produced with the Kinect tracker, but it is also tested with a different human tracker (NiTE). In particular, the aim of this work is to analyse the behaviour of the neural network even when the position of the extracted joints is not reliable and the provided skeleton is confused. Real-time tests have been carried out covering the whole operative range of the sensor (up to 3.5 m). Experimental results have shown an overall accuracy of 98.3% using the NiTE tracker for the falling tests, with the worst accuracy of 97.5%

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context

Sistema di navigazione per robot mobili basato sull'anticipazione sensoriale

Realizzazione di un sistema di navigazione con algoritmi classici con l'aggiunta di un modulo di predizione. Questo modulo permette di prevedere tramite la lettura di una mappa interna, la risposta dei sensori e quindi ottenere maggiore velocita' e affidabilita'

Enabling Global Robot Navigation Based on a Cloud Robotics Approach

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Supporting active and healthy aging with advanced robotics integrated in smart environment

The technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is the integration of service robotics for optimising social services and improving quality of life of the elderly population. This chapter aims to underline the barriers of the state of the art, furthermore the authors present their concrete experiences to overcome these barriers gained at the RoboTown Living Lab of Scuola Superiore Sant'Anna within past and current projects. They analyse and discuss the results in order to give recommendations based on their experiences. Furthermore, this work highlights the trend of development from stand-alone solutions to cloud computing architecture, describing the future research directions

Design of a cloud robotic system to support senior citizens: the KuBo experience

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Robotic services acceptance in smart environments with older adults: user satisfaction and acceptability study.

In Europe, the population of older people is increasing rapidly. Many older people prefer to remain in their homes but living alone could be a risk for their safety. In this context, robotics and other emerging technologies are increasingly proposed as potential solutions to this societal concern. However, one-third of all assistive technologies are abandoned within one year of use because the end users do not accept them. The aim of this study is to investigate the acceptance of the Robot-Era system, which provides robotic services to permit older people to remain in their homes. Six robotic services were tested by 35 older users. The experiments were conducted in three different environments: private home, condominium, and outdoor sites. The appearance questionnaire was developed to collect the users' first impressions about the Robot-Era system, whereas the acceptance was evaluated through a questionnaire developed ad hoc for Robot-Era. A total of 45 older users were recruited. The people were grouped in two samples of 35 participants, according to their availability. Participants had a positive impression of Robot-Era robots, as reflected by the mean score of 73.04 (SD 11.80) for DORO's (domestic robot) appearance, 76.85 (SD 12.01) for CORO (condominium robot), and 75.93 (SD 11.67) for ORO (outdoor robot). Men gave ORO's appearance an overall score higher than women (P=.02). Moreover, participants younger than 75 years understood more readily the functionalities of Robot-Era robots compared to older people (P=.007 for DORO, P=.001 for CORO, and P=.046 for ORO). For the ad hoc questionnaire, the mean overall score was higher than 80 out of 100 points for all Robot-Era services. Older persons with a high educational level gave Robot-Era services a higher score than those with a low level of education (shopping: P=.04; garbage: P=.047; reminding: P=.04; indoor walking support: P=.006; outdoor walking support: P=.03). A higher score was given by male older adults for shopping (P=.02), indoor walking support (P=.02), and outdoor walking support (P=.03). Based on the feedback given by the end users, the Robot-Era system has the potential to be developed as a socially acceptable and believable provider of robotic services to facilitate older people to live independently in their homes. [Abstract copyright: ©Filippo Cavallo, Raffaele Esposito, Raffaele Limosani, Alessandro Manzi, Roberta Bevilacqua, Elisa Felici, Alessandro Di Nuovo, Angelo Cangelosi, Fabrizia Lattanzio, Paolo Dario. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.09.2018.

On the design, development and experimentation of the ASTRO assistive robot integrated in smart environments

This paper presents the full experience of designing, developing and testing ASTROMOBILE, a system composed of an enhanced robotic platform integrated in an Ambient Intelligent (AmI) infrastructure that was conceived to provide favourable independent living, improved quality of life and efficiency of care for senior citizens. The design and implementation of ASTRO robot was sustained by a multidisciplinary team in which technology developers, designers and end-user representatives collaborated using a user-centred design approach. The key point of this work is to demonstrate the general feasibility and scientific/technical effectiveness of a mobile robotic platform integrated in a smart environment and conceived to provide useful services to humans and in particular to elderly people in domestic environments. The main aspects faced in this paper are related to the design of the ASTRO’s appearance and functionalities by means of a substantial analysis of users’ requirements, the improvement of the ASTRO’s behaviour by means of a smart sensor network able to share information with the robot (Ubiquitous Robotics) and the development of advanced human robot interfaces based on natural language

Development of a Socially Believable Multi-Robot Solution from Town to Home

Technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is that they have to be socially acceptable and believable to the end-users. This paper aimed to present some technological aspects that have been faced to develop the Robot-Era system, a multi-robotic system that is able to act in a socially believable way in the environments daily inhabited by humans, such as urban areas, buildings and homes. In particular, this paper focuses on two services—shopping delivery and garbage collection—showing preliminary results on experiments conducted with 35 elderly people. The analysis adopts an end-user-oriented perspective, considering some of the main attributes of acceptability: usability, attitude, anxiety, trust and quality of life

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