ARC: Alignment-based Redirection Controller for Redirected Walking in Complex Environments

We present a novel redirected walking controller based on alignment that allows the user to explore large and complex virtual environments, while minimizing the number of collisions with obstacles in the physical environment. Our alignment-based redirection controller, ARC, steers the user such that their proximity to obstacles in the physical environment matches the proximity to obstacles in the virtual environment as closely as possible. To quantify a controller's performance in complex environments, we introduce a new metric, Complexity Ratio (CR), to measure the relative environment complexity and characterize the difference in navigational complexity between the physical and virtual environments. Through extensive simulation-based experiments, we show that ARC significantly outperforms current state-of-the-art controllers in its ability to steer the user on a collision-free path. We also show through quantitative and qualitative measures of performance that our controller is robust in complex environments with many obstacles. Our method is applicable to arbitrary environments and operates without any user input or parameter tweaking, aside from the layout of the environments. We have implemented our algorithm on the Oculus Quest head-mounted display and evaluated its performance in environments with varying complexity. Our project website is available at https://gamma.umd.edu/arc/

Monte-Carlo Redirected Walking: Gain Selection Through Simulated Walks

We present Monte-Carlo Redirected Walking (MCRDW), a gain selection algorithm for redirected walking. MCRDW applies the Monte-Carlo method to redirected walking by simulating a large number of simple virtual walks, then inversely applying redirection to the virtual paths. Different gain levels and directions are applied, producing differing physical paths. Each physical path is scored and the results used to select the best gain level and direction. We provide a simple example implementation and a simulation-based study for validation. In our study, when compared with the next best technique, MCRDW reduced incidence of boundary collisions by over 50% while reducing total rotation and position gain

Redirected Walking in Infinite Virtual Indoor Environment Using Change-blindness

We present a change-blindness based redirected walking algorithm that allows a user to explore on foot a virtual indoor environment consisting of an infinite number of rooms while at the same time ensuring collision-free walking for the user in real space. This method uses change blindness to scale and translate the room without the user's awareness by moving the wall while the user is not looking. Consequently, the virtual room containing the current user always exists in the valid real space. We measured the detection threshold for whether the user recognizes the movement of the wall outside the field of view. Then, we used the measured detection threshold to determine the amount of changing the dimension of the room by moving that wall. We conducted a live-user experiment to navigate the same virtual environment using the proposed method and other existing methods. As a result, users reported higher usability, presence, and immersion when using the proposed method while showing reduced motion sickness compared to other methods. Hence, our approach can be used to implement applications to allow users to explore an infinitely large virtual indoor environment such as virtual museum and virtual model house while simultaneously walking in a small real space, giving users a more realistic experience.Comment: https://www.youtube.com/watch?v=s-ZKavhXxd

LoCoMoTe – a framework for classification of natural locomotion in VR by task, technique and modality

Virtual reality (VR) research has provided overviews of locomotion techniques, how they work, their strengths and overall user experience. Considerable research has investigated new methodologies, particularly machine learning to develop redirection algorithms. To best support the development of redirection algorithms through machine learning, we must understand how best to replicate human navigation and behaviour in VR, which can be supported by the accumulation of results produced through live-user experiments. However, it can be difficult to identify, select and compare relevant research without a pre-existing framework in an ever-growing research field. Therefore, this work aimed to facilitate the ongoing structuring and comparison of the VR-based natural walking literature by providing a standardised framework for researchers to utilise. We applied thematic analysis to study methodology descriptions from 140 VR-based papers that contained live-user experiments. From this analysis, we developed the LoCoMoTe framework with three themes: navigational decisions, technique implementation, and modalities. The LoCoMoTe framework provides a standardised approach to structuring and comparing experimental conditions. The framework should be continually updated to categorise and systematise knowledge and aid in identifying research gaps and discussions

Advancing proxy-based haptic feedback in virtual reality

This thesis advances haptic feedback for Virtual Reality (VR). Our work is guided by Sutherland's 1965 vision of the ultimate display, which calls for VR systems to control the existence of matter. To push towards this vision, we build upon proxy-based haptic feedback, a technique characterized by the use of passive tangible props. The goal of this thesis is to tackle the central drawback of this approach, namely, its inflexibility, which yet hinders it to fulfill the vision of the ultimate display. Guided by four research questions, we first showcase the applicability of proxy-based VR haptics by employing the technique for data exploration. We then extend the VR system's control over users' haptic impressions in three steps. First, we contribute the class of Dynamic Passive Haptic Feedback (DPHF) alongside two novel concepts for conveying kinesthetic properties, like virtual weight and shape, through weight-shifting and drag-changing proxies. Conceptually orthogonal to this, we study how visual-haptic illusions can be leveraged to unnoticeably redirect the user's hand when reaching towards props. Here, we contribute a novel perception-inspired algorithm for Body Warping-based Hand Redirection (HR), an open-source framework for HR, and psychophysical insights. The thesis concludes by proving that the combination of DPHF and HR can outperform the individual techniques in terms of the achievable flexibility of the proxy-based haptic feedback.Diese Arbeit widmet sich haptischem Feedback für Virtual Reality (VR) und ist inspiriert von Sutherlands Vision des ultimativen Displays, welche VR-Systemen die Fähigkeit zuschreibt, Materie kontrollieren zu können. Um dieser Vision näher zu kommen, baut die Arbeit auf dem Konzept proxy-basierter Haptik auf, bei der haptische Eindrücke durch anfassbare Requisiten vermittelt werden. Ziel ist es, diesem Ansatz die für die Realisierung eines ultimativen Displays nötige Flexibilität zu verleihen. Dazu bearbeiten wir vier Forschungsfragen und zeigen zunächst die Anwendbarkeit proxy-basierter Haptik durch den Einsatz der Technik zur Datenexploration. Anschließend untersuchen wir in drei Schritten, wie VR-Systeme mehr Kontrolle über haptische Eindrücke von Nutzern erhalten können. Hierzu stellen wir Dynamic Passive Haptic Feedback (DPHF) vor, sowie zwei Verfahren, die kinästhetische Eindrücke wie virtuelles Gewicht und Form durch Gewichtsverlagerung und Veränderung des Luftwiderstandes von Requisiten vermitteln. Zusätzlich untersuchen wir, wie visuell-haptische Illusionen die Hand des Nutzers beim Greifen nach Requisiten unbemerkt umlenken können. Dabei stellen wir einen neuen Algorithmus zur Body Warping-based Hand Redirection (HR), ein Open-Source-Framework, sowie psychophysische Erkenntnisse vor. Abschließend zeigen wir, dass die Kombination von DPHF und HR proxy-basierte Haptik noch flexibler machen kann, als es die einzelnen Techniken alleine können

Computational interaction techniques for 3D selection, manipulation and navigation in immersive VR

3D interaction provides a natural interplay for HCI. Many techniques involving diverse sets of hardware and software components have been proposed, which has generated an explosion of Interaction Techniques (ITes), Interactive Tasks (ITas) and input devices, increasing thus the heterogeneity of tools in 3D User Interfaces (3DUIs). Moreover, most of those techniques are based on general formulations that fail in fully exploiting human capabilities for interaction. This is because while 3D interaction enables naturalness, it also produces complexity and limitations when using 3DUIs. In this thesis, we aim to generate approaches that better exploit the high potential human capabilities for interaction by combining human factors, mathematical formalizations and computational methods. Our approach is focussed on the exploration of the close coupling between specific ITes and ITas while addressing common issues of 3D interactions. We specifically focused on the stages of interaction within Basic Interaction Tasks (BITas) i.e., data input, manipulation, navigation and selection. Common limitations of these tasks are: (1) the complexity of mapping generation for input devices, (2) fatigue in mid-air object manipulation, (3) space constraints in VR navigation; and (4) low accuracy in 3D mid-air selection. Along with two chapters of introduction and background, this thesis presents five main works. Chapter 3 focusses on the design of mid-air gesture mappings based on human tacit knowledge. Chapter 4 presents a solution to address user fatigue in mid-air object manipulation. Chapter 5 is focused on addressing space limitations in VR navigation. Chapter 6 describes an analysis and a correction method to address Drift effects involved in scale-adaptive VR navigation; and Chapter 7 presents a hybrid technique 3D/2D that allows for precise selection of virtual objects in highly dense environments (e.g., point clouds). Finally, we conclude discussing how the contributions obtained from this exploration, provide techniques and guidelines to design more natural 3DUIs

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems