Evaluating the Minimum Jerk Motion Model for Redirected Reach in Virtual Reality
Eric J. Gonzalez, Parastoo Abtahi, and Sean Follmer. Extended Abstract at UIST 2019.
Abstract
Reach redirection in virtual reality uses spatial distortion to augment interaction with passive props as well as active haptic devices. For such dynamic physical systems, motion modeling is needed to update the interface based on users’ predicted targets & trajectories. However, it remains unclear how well standard predictive models hold under redirection. In this work we evaluate one such commonly used model, the Minimum-Jerk (MJ) model, during redirected reach at various lateral offsets up to 16 cm. Results show that larger redirection significantly worsens MJ model fit, suggesting that models should be adjusted for reaches with considerable redirection. Predicted arrival times, based on fitting an MJ model on the first half of reach data, led to an average error of -0.29 s for redirected reach, compared to -0.03 s for normal reach.
Read more about this project here, or in our paper linked below.
Extended Abstract
Representative hand velocity profiles during non-redirected reach (top) and 16 cm redirected reach (bottom). Dashed lines indicate MJ model fit and gray area indicates residual error. Redirected profiles tend to have elongated or humped tails, resulting in a worse fit.