Adapting robot task planning to user preferences: an assistive shoe dressing example

The final publication is available at link.springer.comHealthcare robots will be the next big advance in humans’ domestic welfare, with robots able to assist elderly people and users with disabilities. However, each user has his/her own preferences, needs and abilities. Therefore, robotic assistants will need to adapt to them, behaving accordingly. Towards this goal, we propose a method to perform behavior adaptation to the user preferences, using symbolic task planning. A user model is built from the user’s answers to simple questions with a fuzzy inference system, and it is then integrated into the planning domain. We describe an adaptation method based on both the user satisfaction and the execution outcome, depending on which penalizations are applied to the planner’s rules. We demonstrate the application of the adaptation method in a simple shoe-fitting scenario, with experiments performed in a simulated user environment. The results show quick behavior adaptation, even when the user behavior changes, as well as robustness to wrong inference of the initial user model. Finally, some insights in a non-simulated world shoe-fitting setup are also provided.Peer ReviewedPostprint (author's final draft

The National Strategies’ Raising Attainment Plan (RAP) management guide. Supplement: essential features of an effective RAP (National Strategies: secondary)

"The aim of this document is to show how RAPS should be written to meet the Quality Standards. Most sections have an example which does not meet the standards, followed by a revision which conforms to the standards." - Page 2

Using ERP as a basis for Enterprise application integration

Architecting and implementing e-Business supply chain solutions across and within the modern day enterprise, is now becoming a necessity in order to maintain competitive and be adaptable to market needs. As such, the integration of information and processes is a vital step, using technologies such as using Enterprise Resource Planning (ERP), Supply Chain Management (SCM) and enterprise portal platforms. The effective sharing of resource planning and other enterprise related data across and within the enterprise is typically seen as a facet of a business to business (B2B) platform. However, such infrastructures typically involve a tight integration across intra and inter-organisational systems. This paper examines an Enterprise Application Integration (EAI) initiative taken by a global manufacturer of industrial automation products, which attempted to utilise ERP as an integration tool across its internal B2B infrastructure, to achieve such an aim. This paper discusses those integration considerations and complexities, experienced by the case company upon embarking on an EAI integration programme through the adoption of a core ERP as a catalyst for organizational change. In doing so the authors present an analysis of the inherent risks and limitations of this approach in terms of previously published literature in the field, relating to technology-driven organizational change and EAI impact and adoption frameworks

Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Designing for change: mash-up personal learning environments

Institutions for formal education and most work places are equipped today with at least some kind of tools that bring together people and content artefacts in learning activities to support them in constructing and processing information and knowledge. For almost half a century, science and practice have been discussing models on how to bring personalisation through digital means to these environments. Learning environments and their construction as well as maintenance makes up the most crucial part of the learning process and the desired learning outcomes and theories should take this into account. Instruction itself as the predominant paradigm has to step down. The learning environment is an (if not 'the�) important outcome of a learning process, not just a stage to perform a 'learning play'. For these good reasons, we therefore consider instructional design theories to be flawed. In this article we first clarify key concepts and assumptions for personalised learning environments. Afterwards, we summarise our critique on the contemporary models for personalised adaptive learning. Subsequently, we propose our alternative, i.e. the concept of a mash-up personal learning environment that provides adaptation mechanisms for learning environment construction and maintenance. The web application mash-up solution allows learners to reuse existing (web-based) tools plus services. Our alternative, LISL is a design language model for creating, managing, maintaining, and learning about learning environment design; it is complemented by a proof of concept, the MUPPLE platform. We demonstrate this approach with a prototypical implementation and a – we think – comprehensible example. Finally, we round up the article with a discussion on possible extensions of this new model and open problems

Fluid leadership in a multi-user virtual environment educational project with teenagers: Schome Park

This paper examines leadership practices in a virtual community, the Schome Park project. Schome Park, based at the Open University, UK, was the first European closed (i.e. protected) island in Teen Second Life, a multi-user 3D virtual environment. This fully realised, complex interactive 3D environment has no imposed narrative and offers significant engagement for educational projects. The Schome (‘not school not home’) third space community – i.e. not placed in the first space of home or second space of work/school (Oldenburg, 1989) - was set up with the explicit aim of challenging the instructional models and pedagogic practices of the formal, state educational system. In this disembodied environment identities, represented in the virtual world by personalised avatars, possess usefully ambivalent valences. Often adults will join ‘inworld’ educational events organised and delivered by the younger members of the community. Schome makes flexible use of a wiki (collaboratively designed website), asynchronous discussion fora and other communicative media to support learning processes and enhance the development of a physically distanced yet authentic learning community. The authors propose that the community design in these new spaces created an opportunity for leaders to emerge regardless of contextual hierarchy and to forge a developing culture. The paper makes use of evidence from varied datasets to examine manifestations of leadership in the community and issues arising. Young people have been engaged in proposing, planning, executing and reflecting on teaching and learning and governance without deference to adults. Our analysis contributes to understandings of the development of leadership within carefully designed educational online communities and some of the challenges involved for adults in facilitating an appropriately supportive environment for young people. While aware that this innovative experiment continues to face many challenges, we propose that the design of the project offers much to encourage an approach to education in which collaborative, situated engagement in learning and teaching is perceived as a more fruitful model for the twenty-first century than reproduction of traditional hierarchies of teachers and the taught of conventional classrooms

Personalization framework for adaptive robotic feeding assistance

The final publication is available at link.springer.comThe deployment of robots at home must involve robots with pre-defined skills and the capability of personalizing their behavior by non-expert users. A framework to tackle this personalization is presented and applied to an automatic feeding task. The personalization involves the caregiver providing several examples of feeding using Learning-by- Demostration, and a ProMP formalism to compute an overall trajectory and the variance along the path. Experiments show the validity of the approach in generating different feeding motions to adapt to user’s preferences, automatically extracting the relevant task parameters. The importance of the nature of the demonstrations is also assessed, and two training strategies are compared. © Springer International Publishing AG 2016.Peer ReviewedPostprint (author's final draft

Weaving Lighthouses and Stitching Stories: Blind and Visually Impaired People Designing E-textiles

We describe our experience of working with blind and visually impaired people to create interactive art objects that are personal to them, through a participatory making process using electronic textiles (e-textiles) and hands-on crafting techniques. The research addresses both the practical considerations about how to structure hands-on making workshops in a way which is accessible to participants of varying experience and abilities, and how effective the approach was in enabling participants to tell their own stories and feel in control of the design and making process. The results of our analysis is the offering of insights in how to run e-textile making sessions in such a way for them to be more accessible and inclusive to a wider community of participants

Home detection of freezing of gait using Support Vector Machines through a single waist-worn triaxial accelerometer

Among Parkinson’s disease (PD) symptoms, freezing of gait (FoG) is one of the most debilitating. To assess FoG, current clinical practice mostly employs repeated evaluations over weeks and months based on questionnaires, which may not accurately map the severity of this symptom. The use of a non-invasive system to monitor the activities of daily living (ADL) and the PD symptoms experienced by patients throughout the day could provide a more accurate and objective evaluation of FoG in order to better understand the evolution of the disease and allow for a more informed decision-making process in making adjustments to the patient’s treatment plan. This paper presents a new algorithm to detect FoG with a machine learning approach based on Support Vector Machines (SVM) and a single tri-axial accelerometer worn at the waist. The method is evaluated through the acceleration signals in an outpatient setting gathered from 21 PD patients at their home and evaluated under two different conditions: first, a generic model is tested by using a leave-one-out approach and, second, a personalised model that also uses part of the dataset from each patient. Results show a significant improvement in the accuracy of the personalised model compared to the generic model, showing enhancement in the specificity and sensitivity geometric mean (GM) of 7.2%. Furthermore, the SVM approach adopted has been compared to the most comprehensive FoG detection method currently in use (referred to as MBFA in this paper). Results of our novel generic method provide an enhancement of 11.2% in the GM compared to the MBFA generic model and, in the case of the personalised model, a 10% of improvement with respect to the MBFA personalised model. Thus, our results show that a machine learning approach can be used to monitor FoG during the daily life of PD patients and, furthermore, personalised models for FoG detection can be used to improve monitoring accuracy.Peer ReviewedPostprint (published version