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On the Integration of Adaptive and Interactive Robotic Smart Spaces Paladyn, J. Behav. Robot. 2015; 6:165–179 Research Article Open Access Mauro Dragone*, Joe Saunders, and Kerstin Dautenhahn On the Integration of Adaptive and Interactive Robotic Smart Spaces DOI 10.1515/pjbr-2015-0009 Received October 15, 2014; accepted April 14, 2015 1 Introduction Abstract: Enabling robots to seamlessly operate as part Smart home technology utilizes sensors and microproces- of smart spaces is an important and extended challenge sors throughout the home to collect data and information for robotics R&D and a key enabler for a range of ad- in order to provide useful services, such as monitoring the vanced robotic applications, such as Ambient Assisted Liv- daily activity, safety, health and security of the house occu- ing (AAL) and home automation. The integration of these pants. Notwithstanding its benefits to the user’s life style, technologies is currently being pursued from two largely such as allowing elderly persons to live independently in distinct view-points: On the one hand, people-centred ini- their own homes and postponing or perhaps even avoid- tiatives focus on improving the user’s acceptance by tack- ing a potential move to a residential care facility, the tech- ling human-robot interaction (HRI) issues, often adopting nology is still largely confined to research laboratories and a social robotic approach, and by giving to the designer is far from reaching widespread adoption by consumers. and - in a limited degree – to the final user(s), control The biggest barriers to the widespread adoption of such on personalization and product customisation features. technologies are still their prohibitive costs (which, when On the other hand, technologically-driven initiatives are they are employed for AAL applications, often include in- building impersonal but intelligent systems that are able stallation, customization charges and monthly monitoring to pro-actively and autonomously adapt their operations fees), and low levels of user acceptance. Much of the el- to fit changing requirements and evolving users’ needs, derly population is simply not comfortable with what they but which largely ignore and do not leverage human-robot perceive as obtrusive and impersonal technology. Current interaction and may thus lead to poor user experience and systems are also unreliable, which is one of the main rea- user acceptance. In order to inform the development of a sons why such a large proportion of them are confined to new generation of smart robotic spaces, this paper anal- research laboratories and why commercial products are yses and compares different research strands with a view mostly limited to basic monitoring services. to proposing possible integrated solutions with both ad- Notably, users are rarely actively involved in current vanced HRI and online adaptation capabilities. systems. They are passive recipients of smart services, their actions are constantly monitored by using sensors Keywords: Human Robot Interaction; Smart Homes; Am- pervasively embedded in their homes, and their context bient Assisted Living; Robotic Ecology and needs are guessed by the system using models of their past behaviour and/or by using knowledge that was im- bued into the system at design time. Consequently, the per- ceived value and trust in the technology can be seriously undermined and curbed by the constant monitoring and ill-advised or poorly-timed interventions, as well as the user’s lack of control and understanding of the capabili- ties and limitations of the technology. *Corresponding Author: Mauro Dragone: This work done while To tackle some of these issues, autonomous and in- the corresponding author was at University College Dublin (UCD). teractive robots have been or are being integrated with Currently affiliated with the Distributed System Group, School of Computer Science and Statistics, Trinity College Dublin, Ireland, smart spaces and AAL systems in a number of research E-mail: [email protected] projects [1–7, 9, 93]. On one hand, the smart environment Joe Saunders, Kerstin Dautenhahn: Adaptive Systems Research can act as a service provider for the robot, e.g. feeding it Group, Science and Technology Research Institute, University of with information about the user’s whereabouts and state, Hertfordshire, United Kingdom, E-mail: [email protected], by using sensors pervasively embedded in the environ- [email protected] © 2015 Mauro Dragone et al., licensee De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. 166 Ë Mauro Dragone, Joe Saunders, and Kerstin Dautenhahn ment and/or worn by the user. The robot can then provide the fact that the term ‘robotic device’ is taken in a broad useful services thanks to its physical presence and mo- sense, including mobile robots, static sensors or actuators, bility capabilities. For example, when the doorbell rings and automated home appliances. In particular, cognitive the robot could find the person in the house and visually robotic ecologies with information processing algorithms attract his attention to the doorbell. Note that this is not such as perception, learning, and planning are increas- possible with passive devices such as phones, which may ingly capable of adapting autonomously to evolving situa- easily be misplaced or not heard. On the other hand, the tions and achieving useful services that are not restricted robot provides the user with a user interface that acts as to only those situations and methods that are envisioned a representative of the services that the intelligent envi- by their designer [39]. This can greatly simplify design and ronment offers. This increases the user’s acceptance ofthe customization, and support online adaptation to evolving technology and offers added value with services such as environments and changing user needs. However, to date, cognitive stimulation, therapy management, social inclu- these research efforts have mostly focused on the develop- sion/connectedness, coaching, fall handling, and memory ment of the enabling technologies: sensing, acting, coor- aid. dination and learning infrastructures, and have largely ig- Studies on people’s attitude to these robots have nored user - system interaction. We argue that huge oppor- shown how their acceptance not only depends on the prac- tunities are missed by the lack of a deeper interaction and tical benefits they can provide, but also on complex rela- cooperation between robotic ecologies and their users and tionships between the cognitive, affective and emotional much more work is needed to transform them into user- components of peoples’ image of the robot [10]. Further- focused systems, by improving the ways they operate and more, Human Robot interaction (HRI) studies for domes- interact in a human populated environment. Reconciling tic or personal robot companions have raised personaliza- social and personalized human-robot interaction with the tion and social interaction as important considerations for ubiquity and the novel opportunities afforded by cognitive guiding the design of this type of robot application [12, 13]. robotic ecologies (sensing, acting and interacting through For these reasons, the same systems have been increas- distributed sensors and actuators), still remains a largely ingly equipped with easy-to-use and adaptable HRI capa- unexplored area of research. bilities, such as speech and touch screens in order to un- In order to inform the development of this new gen- derstand simple orders, and also to account for users’ vi- eration of smart robotic spaces, this paper provides an sion or hearing impairments. Studies have been performed overview of different research strands with the view of examining situational and platform-specific influences on proposing possible integrated solutions that would sup- human preferences, concerning design factors such as port our vision by offering their combined advantages robots’ proxemic behaviour and appearance, and also fo- while overcoming their current limitations. cused on the role of individual differences in terms of per- Specifically, the remainder of this paper is organized sonality and other demographic factors. However, these in the following manner: Section 2 considers past and cur- studies usually adopt a design-centred approach; they re- rent projects combining service robots in smart spaces. quire a prototype at the outset of the investigation, long Our overview focuses on the analysis of how those projects user trials and usability analysis. Consequently, the results have addressed HRI and users’ acceptance issues in order of this kind of acceptance research are typically limited to to draw a set of requirements for their adaptation, customi- one particular system. The insights gained cannot read- sation and personalization needs, and before discussing ily be generalized across different systems and services. in more detail a specific case study exemplifying best prac- They can inform the development of customised solutions tices addressing these concerns. Section 3 provides an but those solutions have limited abilities to respond to the overview of past and current projects that have embraced users’ in-situ response or adapt to changing contexts and a cognitive robotic ecology (CRE) approach, focusing on evolving users’ needs, habits and preferences. how they tackle issues such as coordination and context- A particularly interesting case is the recent emer- awareness, before focusing on a specific case study ofa gence
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