A Comparison of Visualisation Methods for Disambiguating Verbal Requests in Human-Robot Interaction

Picking up objects requested by a human user is a common task in human-robot interaction. When multiple objects match the user's verbal description, the robot needs to clarify which object the user is referring to before executing the action. Previous research has focused on perceiving user's multimodal behaviour to complement verbal commands or minimising the number of follow up questions to reduce task time. In this paper, we propose a system for reference disambiguation based on visualisation and compare three methods to disambiguate natural language instructions. In a controlled experiment with a YuMi robot, we investigated real-time augmentations of the workspace in three conditions -- mixed reality, augmented reality, and a monitor as the baseline -- using objective measures such as time and accuracy, and subjective measures like engagement, immersion, and display interference. Significant differences were found in accuracy and engagement between the conditions, but no differences were found in task time. Despite the higher error rates in the mixed reality condition, participants found that modality more engaging than the other two, but overall showed preference for the augmented reality condition over the monitor and mixed reality conditions

Elements of design for indoor visualisation

Indoor visualisation has received little attention. Research related to indoor environments have primarily focussed on the data structuring, localisation and navigation components (Zlatanova et al., 2013). Visualisation is an integral component in addressing the diverse array of indoor environments. In simple words, 'What is the most efficient way to visualise the surrounding indoor environment so that the user can concisely understand their surroundings as well as facilitating the process of navigation?' This dissertation proposes a holistic approach that consists of two components. The significance of this approach is that it provides a robust and adaptable method in providing a standard to which indoor visualisation can be referenced against. The first component is a theoretical framework focussing on indoor visualisation and it comprises of principles from several disciplines such as geovisualisation, human-perception theory, spatial cognition, dynamic and 3D environments as well as accommodating emotional processes resulting from human-computer interaction. The second component is based on the theoretical framework and adopts a practical approach towards indoor visualisation. It consists of a set of design properties that can be used for the design of effective indoor visualisations. The framework is referred to as the "Elements of Design" framework. Both these components aim to provide a set of principles and guidelines that can be used as best practices for the design of indoor visualisations. In order to practically demonstrate the holistic indoor visualisation approach, multiple indoor visualisation renderings were developed. The visualisation renderings were represented in a three-dimensional virtual environment from a first-person perspective. Each rendering used the design framework differently. Also, each rendering was graded using a parallel chart that compares how the different visual elements were used per the rendering. The main findings were that the techniques/ renderings that used the visual elements effectively (enhanced human-perception) resulted in better acquisition and construction of knowledge about the surrounding indoor environment

Urban Emotions and Realtime Planning Methods

The Urban Emotions approach combines methods and technologies from Volunteered Geographic Information (VGI), Social Media, sensors and bio-statistical sensors to detect people’s perception for a new perspective about urban environment. In short, it is a methodology for gaining and extracting contextual information of emotion by using technologies from real-time human sensing systems and crowdsourcing methods. “Real-time planning” describes a system in which planning disciplines get a toolset for a fast and simple creation of visualization or simulation from municipal geodata in a consistent workflow. This includes applications from Virtual Reality, Augmented Reality as well as the above mentioned combination of real-time humane sensors and urban sensing systems. Due to the fact, that a real existing city never corresponds with a laboratory situation, Virtual Reality can be one of the solutions to fill the gap for detecting people’s perceptions concerning design, while filtering other unintended side effects. Insights and results from Urban Emotions project, granted by German Research Foundation and Austrian Science Fond, will be presented in this contribution. It is based on a German contribution, published earlier this year (Zeile 2017)

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

A novel visualisation paradigm for three-dimensional map-based mobile services

Estágio realizado na NDrive Navigation Systems, S. A.Tese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 200

A systematic review of augmented reality applications in maintenance

Augmented Reality (AR) technologies for supporting maintenance operations have been an academic research topic for around 50 years now. In the last decade, major progresses have been made and the AR technology is getting closer to being implemented in industry. In this paper, the advantages and disadvantages of AR have been explored and quantified in terms of Key Performance Indicators (KPI) for industrial maintenance. Unfortunately, some technical issues still prevent AR from being suitable for industrial applications. This paper aims to show, through the results of a systematic literature review, the current state of the art of AR in maintenance and the most relevant technical limitations. The analysis included filtering from a large number of publications to 30 primary studies published between 1997 and 2017. The results indicate a high fragmentation among hardware, software and AR solutions which lead to a high complexity for selecting and developing AR systems. The results of the study show the areas where AR technology still lacks maturity. Future research directions are also proposed encompassing hardware, tracking and user-AR interaction in industrial maintenance is proposed