HyperJump: Merging Teleporting and Continuous VR Locomotion into one Paradigm - Riecke, Bernhard E.; Adhikari, Ashu; Zielasko, Daniel; Bretin, Alexander; Heyde, Markus von der; Kruijff, Ernst (ICSC 2021: 8th International Conference on Spatial Cognition, 2021)
Locomotion is essential for all mobile beings, and effectively moving through virtual environments is becoming increasingly important. While teleporting can help to reduce cybersickness and decrease travel time, it can negatively impact naturalism, presence, and spatial orientation. Conversely, continuous locomotion can support path integration, self-motion perception (vection), and thus continuous spatial updating, and provide a more real-life-like locomotion experience and higher accuracy, but can contribute to (cyber-)sickness especially when users cannot physically walk/move. Prior interfaces typically required users to switch between different locomotion control schemes, aiming for specific advantages. Here, we propose a hybrid Virtual Reality locomotion paradigm (“HyperJump”) that aims to combine continuous and discontinuous locomotion into one seamless interface. To investigate HyperJump, we designed an experimental paradigm that combines locomotion through a series of waypoints in a naturalistic virtual city with rapid pointing to landmarks learned along novel paths (>300m length). Locomotion was controlled either by a hand-held VR-controller (thumbstick-velocity-control with controller-directed steering) or a hands-free seated leaning-based interface (“HeadJoystick”). Continuous locomotion was compared with HyperJump, where intermittent jumps are automatically added once the user reaches a threshold velocity (here: 5m/s), beyond which cybersickness is more likely to occur. Results showed that adding HyperJump allowed for comparable spatial orientation performance as continuous locomotion, for both controller- and leaning-based interfaces. However, leaning outperformed controller-based locomotion control by reducing both ego-orientation error and pointing response times. We are currently improving HyperJump based on user feedback and aim to test it for larger-scale environments.
Keywords: NSERC DG 2026; Riecke; Riecke_2021; alexander-bretin; ashu-adhikari; bernhard-riecke; daniel-zielasko; ernst-kruijff; markus-von-der-heyde; motion-cueing; proj--Hyperjump; proj--motionCueingInterfaces; talkWithoutPaper