On the Integration of Adaptive and Interactive Robotic Smart Spaces

© 2015 Mauro Dragone et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)Enabling robots to seamlessly operate as part of smart spaces is an important and extended challenge for robotics R&D and a key enabler for a range of advanced robotic applications, such as AmbientAssisted Living (AAL) and home automation. The integration of these technologies is currently being pursued from two largely distinct view-points: On the one hand, people-centred initiatives focus on improving the user’s acceptance by tackling human-robot interaction (HRI) issues, often adopting a social robotic approach, and by giving to the designer and - in a limited degree – to the final user(s), control on personalization and product customisation features. On the other hand, technologically-driven initiatives are building impersonal but intelligent systems that are able to pro-actively and autonomously adapt their operations to fit changing requirements and evolving users’ needs,but which largely ignore and do not leverage human-robot interaction and may thus lead to poor user experience and user acceptance. In order to inform the development of a new generation of smart robotic spaces, this paper analyses and compares different research strands with a view to proposing possible integrated solutions with both advanced HRI and online adaptation capabilities.Peer reviewe

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

A Software Suite for the Control and the Monitoring of Adaptive Robotic Ecologies

Adaptive robotic ecologies are networks of heterogeneous robotic devices (sensors, actuators, automated appliances) pervasively embedded in everyday environments, where they learn to cooperate towards the achievement of complex tasks. While their flexibility makes them an increasingly popular way to improve a system’s reliability, scalability, robustness and autonomy, their effective realisation demands integrated control and software solutions for the specification, integration and management of their highly heterogeneous and computational constrained components. In this extended abstract we briefly illustrate the characteristic requirements dictated by robotic ecologies, discuss our experience in developing adaptive robotic ecologies, and provide an overview of the specific solutions developed as part of the EU FP7 RUBICON Project

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

"Tap it again, Sam": Harmonizing the frontiers between digital and real worlds in education

Lifelong leaners are intrinsically motivated to embed learning activities into daily life activities. Finding a suitable combination of the two is not trivial since lifelong learners have to face conflicts of time and location. Hence, lifelong learners normally build personal learning ecologies in those moments they set aside to learn making use of their available resources. On the other hand, the advent of Near Field Communication (NFC) technology facilitates the harmonization in the interactions between the digital world and daily physical spaces. Likewise, NFC enabled phones are becoming more and more popular. The contribution of this manuscript is threefold: first, scientific literature where NFC has been used with a direct or indirect purpose to learn is reviewed, and potential uses for lifelong learners are identified; based on these findings the Ecology of Resources for Lifelong Learning is presented as suitable setup for the scaffolding of learning activities with NFC augmented physical spaces; finally, this ecology is piloted and different learning scenarios are proposed for further extension

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

An Integration Gateway for Sensing Devices in Smart Environments

Smart Environments, and in particular Smart Homes, have recently attracted the attention of many researchers and industrial vendors. The proliferation of low-power sensing devices requires integration gateways hiding the complexity of heterogeneous technologies. We propose a ZigBee integration gateway to access and integrate low-power ZigBee devices