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Dyads are couples of collaborative humans that perform a task together while mechanically connected by a robot. As shown in different studies [1] [2], haptic interaction can be beneficial for motor performance so that the dyad outperforms the subject executing the task alone. These achievements are hypothesized to be the result of the haptic communication engaged between the subjects that triggers internal forward models. In this way the dyad&#x2019;s components can attain additional information about the task, hence improving their performance. Here we show a novel dual robotic system, called Pantograph, used in a pilot study to understand the influence that the nature of the partner has on the learning process. The main hypothesis that we claim is that a Novice-Novice type of interaction is more beneficial, in terms of speed of learning, with respect to an Expert-Novice type of interaction. The results show time constants equal to 5.53 &#x00B1; 2.79 and 8.45 &#x00B1; 3.78 for the Novice-Novice and Expert-Novice group, respectively. However, the p-value obtained was p = 7.54%. Hence, we can not generalize our results, but this research study shows how haptic communication between interacting humans allows for motor learning and how the nature of the subjects could be an important factor of the learning process.

Human-Human connected dyads learning a visuomotor rotation in a movement tracking task