A situation that we had never imagined: Post-Fukushima virtual collaborations for determining robot task metrics

There is no consensus regarding a common set of metrics for robot task complexity in associated human-robot interactions. This paper is an attempt to address this issue by proposing a new metric so that the educational potential when using robots can be further developed. Tasks in which students in Japan and UK interact in a 3D virtual space to collaboratively program robots to navigate mazes have resulted in quantitative data of immersion, circuit task complexity and robot task complexity. The data has subsequently been collated to create a proposed new metric for tasks involving robots, which we have termed task fidelity. The paper proposes that task fidelity is a quantitative measure of a set robot task in relation to a learner's solution. By quantifying task fidelity educators utilising robots in schools and in higher education will be able to provide tasks commensurate with the expected successful outcomes achieved by the learners

Using mixed-reality to develop smart environments

Smart homes, smart cars, smart classrooms are now a reality as the world becomes increasingly interconnected by ubiquitous computing technology. The next step is to interconnect such environments, however there are a number of significant barriers to advancing research in this area, most notably the lack of available environments, standards and tools etc. A possible solution is the use of simulated spaces, nevertheless as realistic as strive to make them, they are, at best, only approximations to the real spaces, with important differences such as utilising idealised rather than noisy sensor data. In this respect, an improvement to simulation is emulation, which uses specially adapted physical components to imitate real systems and environments. In this paper we present our work-in-progress towards the creation of a development tool for intelligent environments based on the interconnection of simulated, emulated and real intelligent spaces using a distributed model of mixed reality. To do so, we propose the use of physical/virtual components (xReality objects) able to be combined through a 3D graphical user interface, sharing real-time information. We present three scenarios of interconnected real and emulated spaces, used for education, achieving integration between real and virtual worlds

Whom Do You Want to Be Friends With: An Extroverted or an Introverted Avatar? Impacts of the Uncanny Valley Effect and Conversational Cues

With the rapid growth of social virtual reality platforms, an increasing number of people will be interacting with others as avatars in virtual environments. Therefore, it is essential to develop a better understanding of the factors that could impact initial personality assessments and how they affect the willingness of people to befriend one another. Thin-slice judgment constitutes a quick judgment of a personality based on an avatar, and it could be impacted by the avatar’s appearance, particularly if the avatar elicits an uncanny valley effect that brings negative emotions such as eerieness. However, personality judgments and friendship decisions could also be influenced by social cues, such as conversational style. This experimental study investigated how these factors impact willingness to make friends with others in a virtual world. Drawing upon the uncanny valley effect and thin-slice judgment, this study examined how different levels of realism and conversational cues influence trustworthiness, likeability, and the willingness to be a friend. Furthermore, the current study tried to shed light on the interaction effects of realism and conversational cues to the dependent variables. In other words, this study investigated how this eventually influences one’s willingness to be a friend under the thin-slice judgment when personality judgments result from the negative feeling (i.e., eeriness) of the uncanny valley effect and social cues are conflicted. To this end, a 2 (realism: cartoonish vs. hyper-realistic) x 2 (conversational cues: extroverted vs. introverted) between-subjects online experiment was conducted. The results showed that trustworthiness and likeability significantly impacted the willingness to be a friend. Furthermore, realism and conversational cues marginally affected the willingness to be a friend. Keywords: uncanny valley effect, thin-slice judgment, avatar, personality judgment, willingness to be a frien

An Overview of Self-Adaptive Technologies Within Virtual Reality Training

This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training

Human Machine Interfaces for Teleoperators and Virtual Environments

In Mar. 1990, a meeting organized around the general theme of teleoperation research into virtual environment display technology was conducted. This is a collection of conference-related fragments that will give a glimpse of the potential of the following fields and how they interplay: sensorimotor performance; human-machine interfaces; teleoperation; virtual environments; performance measurement and evaluation methods; and design principles and predictive models

The Impact of Self-Representation and Consistency in Collaborative Virtual Environments

This paper explores the impact of self-representation (full body Self Avatar vs. Just Controllers) in a Collaborate Virtual Environment (CVE) and the consistency of self-representation between the users. We conducted two studies: Study 1 between a confederate and a participant, Study 2 between two participants. In both studies, participants were asked to play a collaborative game, and we investigated the effect on trust with a questionnaire, money invested in a trust game, and performance data. Study 1 suggested that having a Self Avatar made the participant give more positive marks to the confederate and that when the confederate was without an avatar, they received more trust (measured by money). Study 2 showed that consistency led to more trust and better productivity. Overall, results imply consistency improves trust only when in an equal social dynamic in CVE, and that the use of confederate could shift the social dynamics

Unsupervised Sim-to-Real Adaptation of Soft Robot Proprioception using a Dual Cross-modal Autoencoder

Soft robotics is a modern robotic paradigm for performing dexterous interactions with the surroundings via morphological flexibility. The desire for autonomous operation requires soft robots to be capable of proprioception and makes it necessary to devise a calibration process. These requirements can be greatly benefited by adopting numerical simulation for computational efficiency. However, the gap between the simulated and real domains limits the accurate, generalized application of the approach. Herein, we propose an unsupervised domain adaptation framework as a data-efficient, generalized alignment of these heterogeneous sensor domains. A dual cross-modal autoencoder was designed to match the sensor domains at a feature level without any extensive labeling process, facilitating the computationally efficient transferability to various tasks. As a proof-of-concept, the methodology was adopted to the famous soft robot design, a multigait soft robot, and two fundamental perception tasks for autonomous robot operation, involving high-fidelity shape estimation and collision detection. The resulting perception demonstrates the digital-twinned calibration process in both the simulated and real domains. The proposed design outperforms the existing prevalent benchmarks for both perception tasks. This unsupervised framework envisions a new approach to imparting embodied intelligence to soft robotic systems via blending simulation.Comment: 13 pages, 12 figure

From Sloodle to metaverse : teaching and learning in the third space : infrastructure and opportunities

In 2009, an interesting Second Life project brings Moodle into virtual reality. This is the first experience conducted in the virtual world to attend academic courses in hybrid mode, breaking down the boundaries between living, teaching and learning onlineand offline. What features made Second Life so popular, at least in the early stages? What are the points of contact between the virtual worlds and the metaverse? What are the educational prospects expected in the Metaverse today? This contribution analyzes the technological infrastructures and metaverse opportunitie