Seamless-walk: Novel Natural Virtual Reality Locomotion Method with a High-Resolution Tactile Sensor

Abstract

Natural movement is a challenging problem in virtual reality locomotion. However, existing foot-based locomotion methods lack naturalness due to physical limitations caused by wearing equipment. Therefore, in this study, we propose Seamless-walk, a novel virtual reality (VR) locomotion technique to enable locomotion in the virtual environment by walking on a high-resolution tactile carpet. The proposed Seamless-walk moves the user's virtual character by extracting the users' walking speed and orientation from raw tactile signals using machine learning techniques. We demonstrate that the proposed Seamless-walk is more natural and effective than existing VR locomotion methods by comparing them in VR game-playing tasks.