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

Redirection Strategy Switching: Selective Redirection Controller for Dynamic Environment Adaptation

In this paper, we present the Selective Redirection Controller (SRC), which selects the optimal redirection controller based on the physical and virtual environment in Redirected Walking (RDW). The primary advantage of SRC over existing controllers is its dynamic switching among four different redirection controllers (S2C, TAPF, ARC, and SRL) based on the user's environment, as opposed to using a single fixed controller throughout the experience. By switching between redirection controllers based on the context around the user, SRC aims to optimize the advantages of each redirection strategy. The SRC model is trained using reinforcement learning to dynamically and instantaneously switch redirection controllers based on the user's environment. We evaluated the performance of SRC against traditional redirection controllers through simulations and user studies conducted in various physical and virtual environments. The findings indicate that SRC reduces the number of resets significantly compared to traditional redirection controllers. Heat map visualization was utilized during the development process to analyze which redirection controller SRC chooses based on the different environments around the user. SRC alternates between redirection techniques based on the user's environment, maximizing the advantages of each strategy for a superior RDW experience.

APF-S2T: Steering to Target Redirection Walking Based on Artificial Potential Fields

Redirected walking (RDW) enables users to walk naturally within a virtual environment that is larger than the physical environment. Recently, several artificial potential field (APF) and alignment-based redirected controllers have been developed and have been demonstrated to significantly outperform conventional controllers. APF Steer-to-Gradient (APF-S2G) and APF Redirected Walking (APF-RDW) utilize the negative gradient and the total force vector, respectively, which are localized to the user's position. These vectors usually point towards the opposite wall when the user is in corridors, resulting in frequent resets within those regions. This paper introduces the APF Steer-to-Target (APF-S2T), a redirected controller that first finds the target sample point with the lowest score in the user's walkable area in both physical and virtual environments. The score of a sample point is determined by the APF value at the point and the distance from the user's position. The direction from the user's position to the target point is then used as the steering direction for setting RDW gains. We conducted a simulation-based evaluation to compare APF-S2T, APF-S2G, APF-RDW, Visibility Polygon-based alignment (Vis.-Poly.) and Alignment-Optimized controllers in terms of the number of resets and the average distance between resets. The results indicated that APF-S2T significantly outperformed the state-of-the-art controllers.

BiRD: Using Bidirectional Rotation Gain Differences to Redirect Users during Back-and-forth Head Turns in Walking

Redirected walking (RDW) facilitates user navigation within expansive virtual spaces despite the constraints of limited physical spaces. It employs discrepancies between human visual-proprioceptive sensations, known as gains, to enable the remapping of virtual and physical environments. In this paper, we explore how to apply rotation gain while the user is walking. We propose to apply a rotation gain to let the user rotate by a different angle when reciprocating from a previous head rotation, to achieve the aim of steering the user to a desired direction. To apply the gains imperceptibly based on such a Bidirectional Rotation gain Difference (BiRD), we conduct both measurement and verification experiments on the detection thresholds of the rotation gain for reciprocating head rotations during walking. Unlike previous rotation gains which are measured when users are turning around in place (standing or sitting), BiRD is measured during users' walking. Our study offers a critical assessment of the acceptable range of rotational mapping differences for different rotational orientations across the user's walking experience, contributing to an effective tool for redirecting users in virtual environments.

Task and Environment-Aware Virtual Scene Rearrangement for Enhanced Safety in Virtual Reality

Emerging VR applications have revolutionized user experiences by immersing individuals in digitally crafted environments. However, fully immersive experiences introduce new challenges, notably the risk of physical hazards when users are unaware of their surroundings. Existing solutions, including guardian spaces and locomotion systems, present trade-offs that either disrupt the immersive experience or risk inducing motion sickness. To address these challenges, we propose a novel approach that dynamically rearranges VR scenes according to users' physical spaces, seamlessly embedding physical constraints and interaction tasks into the virtual environment. We design a computational model to optimize the rearranged scene through a cost function, ensuring collision-free interactions while maintaining visual fidelity and the goal of interaction tasks. The experiments demonstrate improvements in user experience and safety, presenting an innovative solution to harmonize physical and virtual environments in VR applications.

Novel Design and Evaluation of Redirection Controllers Using Optimized Alignment and Artificial Potential Field

Redirected walking allows users to naturally locomote within virtual environments that are larger than or different in layout from the physically tracked space. In this paper, we proposed novel optimization-driven alignment-based and Artificial Potential Field (APF) redirected walking controllers, as well as an integrated version of the two. The first two controllers employ objective functions of one variable, which is the included angle between the user's heading vector and the target vector originating from the user's physical position. The optimized angle represents the physical cell that is best aligned with the virtual cell or the target vector on which the designated point has the minimum APF value. The derived optimized angle is used to finely set RDW gains. The two objective functions can be optimized simultaneously, leading to an integrated controller that is potentially able to take advantage of the alignment-based controller and APF-based controller. Through extensive simulation-based studies, we found that the proposed alignment-based and integrated controllers significantly outperform the state-of-the-art controllers and the proposed APF based controller in terms of the number of resets. Furthermore, the proposed alignment controller and integrated controller provide a more uniform likelihood distribution across distance between resets, as compared to the other controllers.

Making Resets away from Targets: POI aware Redirected Walking

Rapidly developing Redirected Walking (ROW) technologies have enabled VR applications to immerse users in large virtual environments (VE) while actually walking in relatively small physical environments (PE). When an unavoidable collision emerges in a PE, the ROW controller suspends the user's immersive experience and resets the user to a new direction in PE. Existing ROW methods mainly aim to reduce the number of resets. However, from the perspective of the user experience, when users are about to reach a point of interest (POI) in a VE, reset interruptions are more likely to have an impact on user experience. In this paper, we propose a new ROW method, aiming to keep resets occurring at a longer distance from the virtual target, as well as to reduce the number of resets. Simulation experiments and real user studies demonstrate that our method outperforms state-of-the-art ROW methods in the number of resets and dramatically increases the distance between the reset locations and the virtual targets.

Composite Spatial Manipulation Framework for Redirected Walking

In this study, we present a composite spatial manipulation framework for the redirected walking technique. The proposed framework focuses on utilizing two different approaches simultaneously to manipulate the user’s position and orientation in the physical space, aiming to substantially improve their redirection in a confined physical space and reduce the special requirements for the RDW technique. Each approach utilizes different perceptual processes. The first is a discrete spatial manipulation approach that introduces translation and/or rotation gains to the user’s virtual perspective in the immersive virtual environment (IVE) during temporal events such as eyeblinks. The second approach is the continuous spatial manipulation approach, which continuously introduces (with each frame) translation and/or rotation gains below the user’s perception threshold to their virtual perspective in the IVE. Two simulation experiments were conducted to investigate the feasibility of adopting the composite spatial manipulation framework for RDW without considering the user’s walking behavior or the impact of the proposed approach on user performance in the immersive virtual environment. In the second simulation experiment we aimed to investigate the performance of the proposed approach while considering the user’s walking behavior and performance in the IVE. Finally, a user experiment was conducted to validate the proposed framework and its impact on the user’s performance in the IVE. The findings revealed a significant improvement in the redirection performance of the proposed controller when it was compared to the classical RDW controller. Additionally, there was significant improvement in the user’s performance when the composite RDW controller was utilized.

Adaptive Redirection: A Context-Aware Redirected Walking Meta-Strategy

Previous research has established redirected walking as a potential answer to exploring large virtual environments via natural locomotion within a limited physical space. However, much of the previous work has either focused on investigating human perception of redirected walking illusions or developing novel redirection techniques. In this paper, we take a broader look at the problem and formalize the concept of a complete redirected walking system. This work establishes the theoretical foundations for combining multiple redirection strategies into a unified framework known as adaptive redirection. This meta-strategy adapts based on the context, switching between a suite of strategies with a priori knowledge of their performance under the various circumstances. This paper also introduces a novel static planning strategy that optimizes gain parameters for a predetermined virtual path, known as the Combinatorially Optimized Pre-Planned Exploration Redirector (COPPER). We conducted a simulation-based experiment that demonstrates how adaptation rules can be determined empirically using machine learning, which involves partitioning the spectrum of contexts into regions according to the redirection strategy that performs best. Adaptive redirection provides a foundation for making redirected walking work in practice and can be extended to improve performance in the future as new techniques are integrated into the framework.

Redirected Walking in Static and Dynamic Scenes Using Visibility Polygons

We present a new approach for redirected walking in static and dynamic scenes that uses techniques from robot motion planning to compute the redirection gains that steer the user on collision-free paths in the physical space. Our first contribution is a mathematical framework for redirected walking using concepts from motion planning and configuration spaces. This framework highlights various geometric and perceptual constraints that tend to make collision-free redirected walking difficult. We use our framework to propose an efficient solution to the redirection problem that uses the notion of visibility polygons to compute the free spaces in the physical environment and the virtual environment. The visibility polygon provides a concise representation of the entire space that is visible, and therefore walkable, to the user from their position within an environment. Using this representation of walkable space, we apply redirected walking to steer the user to regions of the visibility polygon in the physical environment that closely match the region that the user occupies in the visibility polygon in the virtual environment. We show that our algorithm is able to steer the user along paths that result in significantly fewer resets than existing state-of-the-art algorithms in both static and dynamic scenes. Our project website is available at https://ganuna.umd.edu/vis.poly/.