Real-time optimal planning for redirected walking using deep q-learning

Dang Yang Lee, Yang Hun Cho, In Kwan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work presents a novel control algorithm of redirected walking called steer-to-optimal-target (S2OT) for effective real-time planning in redirected walking. S2OT is a method of redirection estimating the optimal steering target that can avoid the collision on the future path based on the user's virtual and physical paths. We design and train the machine learning model for estimating optimal steering target through reinforcement learning, especially, using the technique called Deep Q-Learning. S2OT significantly reduces the number of resets caused by collisions between user and physical space boundaries compared to well-known algorithms such as steer-to-center (S2C) and Model Predictive Control Redirection (MPCred). The results are consistent for any combinations of room-scale and large-scale physical spaces and virtual maps with or without predefined paths. S2OT also has a fast computation time of 0.763 msec per redirection, which is sufficient for redirected walking in real-time environments.

Original languageEnglish
Title of host publication26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages63-71
Number of pages9
ISBN (Electronic)9781728113777
DOIs
Publication statusPublished - 2019 Mar
Event26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Osaka, Japan
Duration: 2019 Mar 232019 Mar 27

Publication series

Name26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings

Conference

Conference26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019
CountryJapan
CityOsaka
Period19/3/2319/3/27

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All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Media Technology

Cite this

Lee, D. Y., Cho, Y. H., & Lee, I. K. (2019). Real-time optimal planning for redirected walking using deep q-learning. In 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings (pp. 63-71). [8798121] (26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VR.2019.8798121