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Making virtual walking real: perceptual evaluation of a new treadmill control algorithm

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84228

Souman,  JL
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Multisensory Perception and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84174

Robuffo Giordano,  P
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83920

Frissen,  I
Research Group Multisensory Perception and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83906

Ernst,  MO
Research Group Multisensory Perception and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Souman, J., Robuffo Giordano, P., Frissen, I., Luca, A., & Ernst, M. (2010). Making virtual walking real: perceptual evaluation of a new treadmill control algorithm. Transactions on Applied Perception, 7(2:11), 1-14. doi:10.1145/1670671.1670675.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-C134-9
Abstract
For us humans, walking is our most natural way of moving through the world. One of the major challenges in present research on navigation in virtual reality is to enable users to physically walk through virtual environments. Although treadmills, in principle, allow users to walk for extended periods of time through large virtual environments, existing setups largely fail to produce a truly immersive sense of navigation. Partially, this is because of inadequate control of treadmill speed as a function of walking behavior. Here, we present a new control algorithm that allows users to walk naturally on a treadmill, including starting to walk from standstill, stopping, and varying walking speed. The treadmill speed control consists of a feedback loop based on the measured user position relative to a given reference position, plus a feed-forward term based on online estimation of the user's walking velocity. The purpose of this design is to make the treadmill compensate fully for any persistent walker motion, while keeping the accelerations exerted on the user as low as possible. We evaluated the performance of the algorithm by conducting a behavioral experiment in which we varied its most important parameters. Participants walked at normal walking speed and then, on an auditory cue, abruptly stopped. After being brought back to the center of the treadmill by the control algorithm, they rated how smoothly the treadmill had changed its velocity in response to the change in walking speed. Ratings, in general, were quite high, indicating good control performance. Moreover, ratings clearly depended on the control algorithm parameters that were varied. Ratings were especially affected by the way the treadmill reversed its direction of motion. In conclusion, controlling treadmill speed in such a way that changes in treadmill speed are unobtrusive and do not disturb VR immersiveness is feasible on a normal treadmill with a straightforward control algorithm.