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A Comprehensive Review of Redirected Walking Techniques: Taxonomy, Methods, and Future Directions

State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China
Department of Informatics, Universität Hamburg, Hamburg 20146, Germany
Peng Cheng Laboratory, Shenzhen 518055, China
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Abstract

Virtual reality (VR) allows users to explore and experience a computer-simulated virtual environment so that VR users can be immersed in a totally artificial virtual world and interact with arbitrary virtual objects. However, the limited physical tracking space usually restricts the exploration of large virtual spaces, and VR users have to use special locomotion techniques to move from one location to another. Among these techniques, redirected walking (RDW) is one of the most natural locomotion techniques to solve the problem based on near-natural walking experiences. The core idea of the RDW technique is to imperceptibly guide users on virtual paths, which might vary from the paths they physically walk in the real world. In a similar way, some RDW algorithms imperceptibly change the structure and layout of the virtual environment such that the virtual environment fits into the tracking space. In this survey, we first present a taxonomy of existing RDW work. Based on this taxonomy, we compare and analyze both contributions and shortcomings of the existing methods in detail, and find view manipulation methods offer satisfactory visual effect but the experience can be interrupted when users reach the physical boundaries, while virtual environment manipulation methods can provide users with consistent movement but have limited application scenarios. Finally, we discuss possible future research directions, indicating combining artificial intelligence with this area will be effective and intriguing.

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Journal of Computer Science and Technology
Pages 561-583

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Cite this article:
Li Y-J, Steinicke F, Wang M. A Comprehensive Review of Redirected Walking Techniques: Taxonomy, Methods, and Future Directions. Journal of Computer Science and Technology, 2022, 37(3): 561-583. https://doi.org/10.1007/s11390-022-2266-7

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Received: 24 February 2022
Accepted: 18 May 2022
Published: 31 May 2022
©Institute of Computing Technology, Chinese Academy of Sciences 2022