Praminda Caleb-Solly

A mixed-method approach to evoke creative and holistic thinking about robots in a home environment

Discovering older adults’ perceptions and expectations of domestic care service robots are vital in informing the design and development of new technologies to ensure acceptability and usability. This paper identifies issues that were elicited from older adults using different methods to promote creative thinking about domestic robots at an emotional level, as well as pragmatic level. These included exploring people’s ideal embodiment preferences and requirements for a domestic care service robot, and also what embodiments and functional aspects will not be acceptable. We analysed our findings using relevant constructs from the Unified Theory of Acceptance and Use of Technology, and Technology Acceptance models. In addition to some already well-established findings, we discovered some surprising aspects concerning interaction, behaviour and appearance and the ability for the robot to fit the relevant context, both physically and conceptually. Categories and Subject Descriptors Assistive technologies for persons with disabilities, Requirements Elicitation General Terms Design, Human Factors

An assistive robot to support dressing - strategies for planning and error handling

Assistive robots are emerging to address a social need due to changing demographic trends such as an ageing population. The main emphasis is to offer independence to those in need and to fill a potential labour gap in response to the increasing demand for caregiving. This paper presents work undertaken as part of a dressing task using a compliant robotic arm on a mannequin. Several strategies are explored on how to undertake this task with minimal complexity and a mix of sensors. A Vicon tracking system is used to determine the arm position of the mannequin for trajectory planning by means of waypoints. Methods of failure detection were explored through torque feedback and sensor tag data. A fixed vocabulary of recognised speech commands was implemented allowing the user to successfully correct detected dressing errors. This work indicates that low cost sensors and simple HRI strategies, without complex learning algorithms, could be used successfully in a robot assisted dressing task.

Interactive Evolutionary Strategy Based Discovery of Image Segmentation Parameters

The symbiosis of human expertise, in terms of creativity and pattern recognition, with evolutionary algorithms for user controlled and directed search is now a rapidly emerging model.

A novel feature selection based semi-supervised method for image classification

Automated surface inspection of products as part of a manufacturing quality control process involves the applications of image processing routines to segment regions of interest (ROI) or objects which correspond to potential defects on the product or part. In these type of applications, it is not known in advance how many ROIs may be segmented from images, and so classification algorithms mainly make use of only image-level features, ignoring important object-level information. In this paper, we will investigate how to preprocess high-dimensional object-level features through a unsupervised learning system and present the outputs of that system as additional image-level features to the supervised learning system. Novel semi-supervised approaches based on K-Means/Tabu Search(TS) and SOM/Genetic Algorithm (GA) with C4.5 as supervised classifier have been proposed in this paper. The proposed algorithms are then applied on real-world CD/DVD inspection system. Results have indicated an increase in the performance in terms of classification accuracy when compared with various existing approaches.

A mobile location-based situated learning framework for supporting critical thinking: A requirements analysis study

This chapter presents the requirements work carried out as part of developing an intervention to improve students’ analysis and critical thinking skills using location-based mobile learning. The research emerged from seeking to identify ways of getting human–computer interaction design students into real-world environments, similar to those in which they will eventually be designing, thus maximising their ability to identify opportunities for innovation. The first stage in designing the system was to conduct a comprehensive requirements study to understand specific student and staff needs in the envisaged scenario. As part of this study, we were interested in identifying weaknesses in the current mode of teaching, as well as problems some students currently experience in understanding key concepts and staying focused on the task. We also noted scope for further supporting students with the analysis of their findings. This information has helped us determine the type and nature of location-based hints and formative feedback that the system can provide to aid students’ understanding of the context they are in.

A Quantitative Analysis of Dressing Dynamics for Robotic Dressing Assistance

Assistive robots have a great potential to address issues related to an ageing population and an increased demand for caregiving. Successful deployment of robots working in close proximity with people requires consideration of both safety and human-robot interaction. One of the established activities of daily living where robots could play an assistive role is dressing. Using the correct force profile for robot control will be essential in this application of human-robot interaction requiring careful exploration of factors related to the user’s pose and the type of garments involved. In this paper a Baxter robot was used to dress a jacket onto a mannequin and human participants considering several combinations of user pose and clothing type (base layers), whilst recording dynamic data from the robot, a load cell and an IMU. We also report on suitability of these sensors for identifying dressing errors, e.g. fabric snagging. Data was analyzed by comparing the overlap of confidence intervals to determine sensitivity to dressing. We expand the analysis to include classification techniques such as decision tree and support vector machines using k-fold cross-validation. The 6-axis load cell successfully discriminated between clothing types with predictive model accuracies between 72-97%. Used independently, the IMU and Baxter sensors were insufficient to discriminate garment types with the IMU showing 40-72% accuracy, but when used in combination this pair of sensors achieved an accuracy similar to the more expensive load cell (98%). When observing dressing errors (snagging) Baxter’s sensors and the IMU data demonstrated poor sensitivity but applying machine learning methods resulted in model with high predicative accuracy and low false negative rates (≤5%). The results show that the load cell could be used independently for this application with good accuracy but a combination of the lower cost sensors could also be used without a significant loss in precision which will be a key element in the robot control architecture for safe human-robot interaction.

Evaluating the Effectiveness of a Mobile Location-Based Intervention for Improving Human-Computer Interaction Students' Understanding of Context for Design

With the ubiquity of interactive computer-based systems, designers are challenged to ensure the effectiveness and efficiency of their designs for a variety of different environments and user activities. To achieve this, designers need to have a comprehensive understanding of the relevant contexts and of the people for whom they are designing systems. Therefore, in helping students learn how to become proficient and innovative designers and developers, it is crucial to get them out of the classroom and into the environments in which their designs will be used. In this paper we describe an app designed to provide location-based hints and formative feedback to students to aid their understanding of the context. The results show an improvement in scores and quality of assessed work completed with the support of the app and a positive response from students regarding its usability and pedagogic utility. The paper also considers the challenges of conducting an ecologically valid study of such interventions in a higher education setting.

Cameras as cultural probes in requirements gathering — Exploring their potential in supporting the design of assistive technology

A pre-requisite for a human-centred design approach to technology development is gaining an intimate understanding of not only the people for whom the technology is being designed, but also the contexts within which they will be using it. This paper explores the use of cameras as cultural probes for gaining this understanding. In this study, probes were included as part of the requirements elicitation methodology for an EU FP7 research project, MOBISERV, developing an integrated intelligent home environment for the provision of health, nutrition and mobility services for older adults. During the initial phase of the project, modelling user requirements for MOBISERV components, disposable cameras were adopted as one of several methods for eliciting information. They were given to older adults (potential end users of the system) enabling them to provide an insight into personal aspects of their own lives. This paper presents the approach and gives a description and evaluation of the method used, considering the information obtained and its impact on enabling contextualisation of the issues and raising awareness of user needs.

An Emerging Framework to Inform Effective Design of Human-Machine Interfaces for Older Adults Using Connected Autonomous Vehicles

Connected autonomous vehicles (CAVs) represent an exciting opportunity for wider access to mobility; especially for individuals unable to drive manual vehicles. Interaction with CAVs will be through human-machine interfaces (HMIs) providing journey-related and other information with some interactivity. These should be designed with potential users as part of a co-design process to maximize acceptance, engagement, and trust. This paper presents an emerging framework to inform the design of in-vehicle CAV HMIs with a focus on older adults (70-years+). These could be amongst early adopters of CAVs and tend to have the highest level of cognitive, sensory, and physical impairments. Whilst there are numerous principles on HMI design for older adults there are fewer on HMIs for AVs, and a need for research on CAV HMI design principles for older adults. Our emerging framework is novel and important for designers of CAV HMIs for older adults and other potential users.

Incorporation of adaptive mutation based on subjective evaluation in an interactive evolution strategy

A rapidly emerging model in the field of adaptive computing is the symbiosis of human expertise with evolutionary algorithms for user controlled and directed search. The two aspects in any EA are the selection of individuals to reproduce based on some measure of their quality or fitness and the application of variation operators to produce new solutions. In the context of interactive evolution, these aspects are compounded by the need for rapid convergence to prevent user fatigue and to provide the user some control over the generation of new solutions. Elsewhere, in the work of the authors (2004), we have examined different policies for best incorporating the user into the evaluation and selection process. In this paper, we explore the hypothesis that user assigned fitness represents a source of information that can be used to control the variation process: effectively to broaden the search if none of the current solutions is promising, or focus the search and improve convergence speed in the vicinity of a good solution. The main aims of this study, therefore, are to analyse the advantages of using a user directed adaptive mutation strategy over fixed mutation step sizes in terms of time to converge and robustness of the resulting solution. We present results showing a qualitatively different type of search process can be obtained by using the user assigned fitness to control the nature of the mutation process. There is also a synergy between user-based selection and fitness-based mutation control which out performs either system on its own.