110 research outputs found
Advances in Human-Robot Interaction
Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers
Detecting Abnormal Social Robot Behavior through Emotion Recognition
Sharing characteristics with both the Internet of Things and the Cyber Physical Systems categories, a new type of device has arrived to claim a third category and raise its very own privacy concerns. Social robots are in the market asking consumers to become part of their daily routine and interactions. Ranging in the level and method of communication with the users, all social robots are able to collect, share and analyze a great variety and large volume of personal data.In this thesis, we focus the community’s attention to this emerging area of interest for privacy and security research. We discuss the likely privacy issues, comment on current defense mechanisms that are applicable to this new category of devices, outline new forms of attack that are made possible through social robots, highlight paths that research on consumer perceptions could follow, and propose a system for detecting abnormal social robot behavior based on emotion detection
Conversational affective social robots for ageing and dementia support
Socially assistive robots (SAR) hold significant potential to assist older adults and people with dementia in human engagement and clinical contexts by supporting mental health and independence at home. While SAR research has recently experienced prolific growth, long-term trust, clinical translation and patient benefit remain immature. Affective human-robot interactions are unresolved and the deployment of robots with conversational abilities is fundamental for robustness and humanrobot engagement. In this paper, we review the state of the art within the past two decades, design trends, and current applications of conversational affective SAR for ageing and dementia support. A horizon scanning of AI voice technology for healthcare, including ubiquitous smart speakers, is further introduced to address current gaps inhibiting home use. We discuss the role of user-centred approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarise the state of development in interactions using speech and natural language processing, which forms a baseline for longitudinal health monitoring and cognitive assessment. Drawing from this foundation, we identify open challenges and propose future directions to advance conversational affective social robots for: 1) user engagement, 2) deployment in real-world settings, and 3) clinical translation
MULTI-MODAL TASK INSTRUCTIONS TO ROBOTS BY NAIVE USERS
This thesis presents a theoretical framework for the design of user-programmable
robots. The objective of the work is to investigate multi-modal unconstrained natural
instructions given to robots in order to design a learning robot. A corpus-centred
approach is used to design an agent that can reason, learn and interact with a human in a
natural unconstrained way. The corpus-centred design approach is formalised and
developed in detail. It requires the developer to record a human during interaction and
analyse the recordings to find instruction primitives. These are then implemented into a
robot. The focus of this work has been on how to combine speech and gesture using
rules extracted from the analysis of a corpus. A multi-modal integration algorithm is
presented, that can use timing and semantics to group, match and unify gesture and
language. The algorithm always achieves correct pairings on a corpus and initiates
questions to the user in ambiguous cases or missing information. The domain of card
games has been investigated, because of its variety of games which are rich in rules and
contain sequences. A further focus of the work is on the translation of rule-based
instructions. Most multi-modal interfaces to date have only considered sequential
instructions. The combination of frame-based reasoning, a knowledge base organised as
an ontology and a problem solver engine is used to store these rules. The understanding
of rule instructions, which contain conditional and imaginary situations require an agent
with complex reasoning capabilities. A test system of the agent implementation is also
described. Tests to confirm the implementation by playing back the corpus are
presented. Furthermore, deployment test results with the implemented agent and human
subjects are presented and discussed. The tests showed that the rate of errors that are
due to the sentences not being defined in the grammar does not decrease by an
acceptable rate when new grammar is introduced. This was particularly the case for
complex verbal rule instructions which have a large variety of being expressed
Human Machine Interaction
In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction
A framework for developing a conversational agent to improve normal age- associated memory loss and increase subjective wellbeing
Research has developed a baseline conversational agent (CA)
framework that experiments suggest may improve normal ageing
memory problems and increase Subjective Wellbeing (SWB) in
participants aged 60+ with normal age-associated memory loss.
In 2008, 1.3 million people in the United Kingdom were aged 85+, this
figure is projected to reach 3.3 million by 2033 (Morse, 2010). Thus, as
the population profile changes, ageing memory impairment problems will
become acuter (Morse, 2010). The number of people worldwide with
diagnosed clinical memory problems is expected to double every 20
years to 66 million by 2030 and 115 million by 2050 (Casey et al., 2016,
Prince et al., 2013). Improving memory impairment reduces distress for
individuals and enhances wellbeing and independence (Dorin, 2007);
(Wagner et al., 2010). The quality of life in old age can be improved by
increasing SWB (George, 2010) that is concerned with how people
experience the quality of their lives and includes both emotional
reactions and cognitive judgments (George, 2010).
Experiments performed as part of the pilot study suggested evidence of
increased SWB and improved memory after use of the CA. To
support these early findings, modification to the agent and further
experimentation was undertaken. Further work enhanced the
preliminary work that was carried out and provided the opportunity to
run further, more in-depth evaluations of the CA as both a
reminiscence aid and as an improver of SWB.
This PhD study applied for and gained ethical approval (SE111219) from
the Faculty of Science & Engineering Ethics Committee, Manchester
Metropolitan University on 25 October 2012
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