Exploring Perception-Based Techniques for Redirected Walking in VR: A Comprehensive Survey

TL;DR

This survey comprehensively reviews perception-based redirected walking techniques in VR, providing a taxonomy that aids understanding, design, and future research directions for expanding virtual environments beyond physical space constraints.

Contribution

It introduces a detailed taxonomy for perception-based RDW techniques, synthesizing 232 papers to clarify current methods and identify underexplored areas for future research.

Findings

Classification of RDW techniques based on gains and application methods

Identification of key patterns and relationships in current RDW research

Guidance for designing more effective RDW systems and future research directions

Abstract

We present a comprehensive survey of perception-based redirected walking (RDW) techniques in virtual reality (VR), presenting a taxonomy that serves as a framework for understanding and designing RDW algorithms. RDW enables users to explore virtual environments (VEs) larger than their physical space, addressing the constraints of real walking in limited home VR setups. Our review spans 232 papers, with 165 included in the final analysis. We categorize perception-based RDW techniques based on gains, gain application, target orientation calculation, and optional general enhancements, identifying key patterns and relationships. We present data on how current work aligns within this classification system and suggest how this data can guide future work into areas that are relatively under explored. This taxonomy clarifies perception-based RDW techniques, guiding the design and application of RDW systems, and suggests future research directions to enhance VR user experience.