Haptic transparency increases the generalizability of motor learning during telemanipulation

Abstract

Haptic transparency is an extensively studied subject in teleoperation. However, the exact role of transparency in human-in-the-loop task execution is only partially understood. In this study, a human factors experiment was performed with the goal to assess the effect of transparency on the rate and generalizability of motor learning. Subjects performed a reach adaptation task under the effect of a viscous curl force field, while two levels of transparency were provided, namely (near) natural transparency and reduced transparency based on a bilateral position-error controller. In the `familiarization' stage subjects performed an eight cm planar movement in a straight line without any external dynamics. In the `learning' stage, subjects performed the same movement, but now under the effect of a viscous curl force field. Finally, subjects were instructed to `generalize' their learning of the force field for a comparable movement in a different position and orientation. The results show that, while the rate of learning and steady-state performance of a task may not benefit from the highest level of transparency, the ability to generalize beyond a set of pre-experienced motions increases when haptic transparency is (close to) natural. It is concluded that haptic transparency may allow for more rapid and more accurate behaviour in situations that have not yet been encountered.