Information about one’s own motion through space can be specified by several sensory systems including, proprioceptive, vestibular and visual. Research in our group has directly explored the specific characteristics of self-motion perception when experienced via individual sensory systems.
For instance, the illusory sense of self-motion that occurs during purely visual stimulation is known as “vection”. Several projects have looked at how specific types of visual motion (up, down, linear, rotational) specified purely by optic flow causes a subjective experience of self-motion (Schulte-Pelkum, Trutoiu). Others have used more natural behavioural situations such as driving tasks to ask questions related to how visual speed is estimated under varying conditions (Pretto) and have also asked questions related to how the scale/size of environmental features affects self-motion perception (Berger). The addition of a floor projection to the large field of view panoramic display has been shown to provide a more compelling experience of linear vection, but not rotational vection (Trutoiu). On the other hand, under some circumstances, optic flow alone has been shown to be insufficient for enabling effective and automatic spatial updating (Riecke).
It is also clear that humans can, to some extent, also use non-visual cues to judge self-motion in complete darkness. For instance, the characteristics of passive self-motion have been tested by moving participants along trajectories with different velocity profiles while having them continuously point to the remembered position of a target (Campos, Loomis, Siegle). This was done using both, the robotic wheelchair and the MPI motion simulator. Understanding the characteristics of passive self-motion perception is also important for understanding how to best create the subjective experience of different types of movements without actually requiring the full range of physical movement (e.g. using motion cuing to simulate long-range forward accelerations; Berger). Providing effective movement dynamics is also something that is critical for simulating self-motion scenarios for ecologically valid tasks such as driving (Pretto) and helicopter flight (Beykirch, Nieuwenhuizen).