Evaluating the use of robots to enlarge AAL services

We introduce robots as a tools to enhance Ambient Assisted Living (AAL) services. Robots are a unique opportunity to create new systems to cooperate in reaching better living conditions. Robots offer the possibility of richer interaction with humans, and can perform actions to actively change the environment. The current state-of-art includes skills in various areas, including advanced interaction (natural language, visual attention, object recognition, intention learning), navigation (map learning, obstacle avoidance), manipulation (grasping, use of tools), and cognitive architectures to handle highly unpredictable environments. From our experience in several robotics projects and principally in the RoboCup@Home competition, a new set of evaluation methods is proposed to assess the maturity of the required skills. Such comparison should ideally enable the abstraction from the particular robotic platform and concentrate on the easy comparison of skills. The validity of that low-level skills can be then scaled to more complex tasks, that are composed by several skills. Our conclusion is that effective evaluation methods can be designed with the objective of enabling robots to enlarge AAL services.This research was partly supported by the PATRICIA project (TIN2012-38416-C03-01), MANIPlus project (201350E102), Spanish Ministry of Economy and Competitiveness, and European Found for Regional Development (FEDER).Peer Reviewe

Into the Wild: Pushing a Telepresence Robot Outside the Lab

Most robotic systems are usually used and evaluated in laboratory setting for a limited period of time. The limitation of lab evaluation is that it does not take into account the different challenges imposed by the fielding of robotic solutions into real contexts. Our current work evaluates a robotic telepresence platform to be used with elderly people. This paper describes our progressive effort toward a comprehensive, ecological and longitudinal evaluation of such robots outside the lab. It first discusses some results from a twofold short term evaluation performed in Italy. Specifically we report results from both a usability assessment in laboratory and a subsequent study obtained by interviewing 44 healthcare workers as possible secondary users (people connecting to the robot) and 10 older adults as possible primary users (people receiving visits through the robot). It then describes a complete evaluation plan designed for a long term assessment to be applied "outside the lab" dwelling on the initial application of such methodology to test sites in Italy

Towards robots reasoning about group behavior of museum visitors: leader detection and group tracking

The final publication is available at IOS Press through http://dx.doi.org/10.3233/AIS-170467Peer ReviewedPostprint (author's final draft

Chapter User Experience Results of Setting Free a Service Robot for Older Adults at Home

The chapter presents the analysis of user trials where, for the first time, a service robot was set free in the home of users. Different to previous studies there was no pre-specified schedule of tasks to execute. The goal was to show that useful functionalities for users can also be achieved with the low-cost components of the Hobbit robot. With the one-arm mobile service robot Hobbit we provided users with a service robot running basic robot functionalities such as navigation, grasping objects from the floor, emergency handling, entertainment, fitness and communication functions. Users could freely select what to do over the three-week trials in homes in three European countries. Users have been questioned on what functionality would help them to stay longer at home and live independently. Results provide better insights of what users want than in pre-set scenarios, where many of the factors we encountered do not show up. Good examples are the need to have robots navigate autonomously at home, grasping objects from the floor is a highly valued function, and the robot needs to adapt locations depending on the daily liking of the users who move much more freely at home than in pre-set scenarios

The Impact of Robots, Artificial Intelligence, and Service Automation on Service Quality and Service Experience in Hospitality

Purpose- The purpose of this chapter is to critically evaluate the implementation of technologies from the perspective of guest services, innovation and visitor experiences. The paper focuses on the value of robots, service automation and artificial intelligence in hospitality and examines their influence on service quality Design/methodology/approach- The chapter is a critical and conceptual overview of the emergence and implementation of robots, service automation and artificial intelligence in the hospitality with an emphasis on service, service quality and guest experience. A comprehensive overview of the academic literature of customer service and guest experience is combined with industry examples from various service operations in hospitality in order to examine the implementation of RAISA in the hospitality industry from a range of academic and practical viewpoints. Findings- The chapter argues that despite the global acceptance of technologies in service industries in general and hospitality in particular, it remains difficult to find the right balance between digital and human interactions. In the context of service quality, the implementation of robots and service automation is increasingly important for gaining a competitive advantage, but the provision of more personalized guest experiences remains controversial. Originality/value- The study provides a comprehensive and systematic review of RAISA in a hospitality context and examine their impacts on service quality. The chapter is a critical examination of the potential of RAISA to transform the service experience and raises some fundamental questions regarding the need for RAISA, its practical implications and impact over the understanding and measurement of service quality

A Sensing Platform to Monitor Sleep Efficiency

Sleep plays a fundamental role in the human life. Sleep research is mainly focused on the understanding of the sleep patterns, stages and duration. An accurate sleep monitoring can detect early signs of sleep deprivation and insomnia consequentially implementing mechanisms for preventing and overcoming these problems. Recently, sleep monitoring has been achieved using wearable technologies, able to analyse also the body movements, but old people can encounter some difficulties in using and maintaining these devices. In this paper, we propose an unobtrusive sensing platform able to analyze body movements, infer sleep duration and awakenings occurred along the night, and evaluating the sleep efficiency index. To prove the feasibility of the suggested method we did a pilot trial in which several healthy users have been involved. The sensors were installed within the bed and, on each day, each user was administered with the Groningen Sleep Quality Scale questionnaire to evaluate the user’s perceived sleep quality. Finally, we show potential correlation between a perceived evaluation with an objective index as the sleep efficiency.</p

Accessibility requirements for human-robot interaction for socially assistive robots

Mención Internacional en el título de doctorPrograma de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: María Ángeles Malfaz Vázquez.- Secretario: Diego Martín de Andrés.- Vocal: Mike Wal

Application and validation of capacitive proximity sensing systems in smart environments

Smart environments feature a number of computing and sensing devices that support occupants in performing their tasks. In the last decades there has been a multitude of advances in miniaturizing sensors and computers, while greatly increasing their performance. As a result new devices are introduced into our daily lives that have a plethora of functions. Gathering information about the occupants is fundamental in adapting the smart environment according to preference and situation. There is a large number of different sensing devices available that can provide information about the user. They include cameras, accelerometers, GPS, acoustic systems, or capacitive sensors. The latter use the properties of an electric field to sense presence and properties of conductive objects within range. They are commonly employed in finger-controlled touch screens that are present in billions of devices. A less common variety is the capacitive proximity sensor. It can detect the presence of the human body over a distance, providing interesting applications in smart environments. Choosing the right sensor technology is an important decision in designing a smart environment application. Apart from looking at previous use cases, this process can be supported by providing more formal methods. In this work I present a benchmarking model that is designed to support this decision process for applications in smart environments. Previous benchmarks for pervasive systems have been adapted towards sensors systems and include metrics that are specific for smart environments. Based on distinct sensor characteristics, different ratings are used as weighting factors in calculating a benchmarking score. The method is verified using popularity matching in two scientific databases. Additionally, there are extensions to cope with central tendency bias and normalization with regards to average feature rating. Four relevant application areas are identified by applying this benchmark to applications in smart environments and capacitive proximity sensors. They are indoor localization, smart appliances, physiological sensing and gesture interaction. Any application area has a set of challenges regarding the required sensor technology, layout of the systems, and processing that can be tackled using various new or improved methods. I will present a collection of existing and novel methods that support processing data generated by capacitive proximity sensors. These are in the areas of sparsely distributed sensors, model-driven fitting methods, heterogeneous sensor systems, image-based processing and physiological signal processing. To evaluate the feasibility of these methods, several prototypes have been created and tested for performance and usability. Six of them are presented in detail. Based on these evaluations and the knowledge generated in the design process, I am able to classify capacitive proximity sensing in smart environments. This classification consists of a comparison to other popular sensing technologies in smart environments, the major benefits of capacitive proximity sensors, and their limitations. In order to support parties interested in developing smart environment applications using capacitive proximity sensors, I present a set of guidelines that support the decision process from technology selection to choice of processing methods