Human-Machine

Human-machine and human-human physical interaction

We are interested in determining the mechanisms underlying the control of physical interactions among two human agents. Unlike controlling one’s own limb, controlling the dynamic of an object that is also grasped by another subject is more complex as neither agent can accurately predict the mechanical and sensory consequences of his/her actions. In a collaboration with Dr. Artemiadis at Arizona State University, we found that human participants can infer the partner’s intended movement direction by probing his/her limb stiffness.1 In a joint manipulation task,2 we found that task performance of dyads was not affected by different pairings of dominant and non-dominant hands. However, the spatial configuration of the two agents (side-by-side vs. face-to-face) appears to play an important role, such that dyads performed better side-by-side than face-to-face (Fig. 6).

 

Figure 6. Top: Control (bimanual) and experimental groups (dyads) used for the study of joint manipulation. Bottom: Performance (object roll) of each dyad (y-axis) as a function of relative performance of each subject in the dyad plotted for all subject groups (a) and separately with data from each subject group (b-e). From: Mojtahedi, Fu and Santello (2017).

 

For more information on these projects contact: Marco Santello, Yen-Hsun Wu


References

  1. Mojtahedi K, Whitsell B, Artemiadis P, Santello M (2017). Communication and inference of intended movement direction during human-human physical interaction. Frontiers in Neurorobotics.
  2. Mojtahedi K, Fu Q, Santello M (2017). On the role of dyadic interactions on performance of object manipulation. Frontiers in Human Neuroscience.