Communication through physical interaction: A study of human collaborative manipulation of a planar object

In this paper we describe our progress towards understanding human communication through physical interaction. We describe a classification algorithm that can recognize four classes of actions that frequently occur during collaborative manipulation of planar objects. These actions were selected based on a user study involving dyads of elderly and care-giver in a realistic setting. Further user studies were conducted to collect the data necessary to develop the classification algorithm. As part of the data collection we also developed a sensory glove. The classification algorithm gives insight into human collaborative manipulation. More precisely, it identifies features in the data that are significant for classification. This information is particularly interesting as it only relies on physical aspects of the interaction and not on any particular sensor. As a result, the described work does not depend on any particular hardware and can be directly used by other researchers in human-robot interaction to develop further experiments and studies.