Understanding Human Co-Manipulation Via Motion and Haptic Information to Enable Future Physical Human-Robotic Collaborations

Kody Shaw^*Marc Daniel KillpackJohn LaNay Salmon^*

• Brigham Young University, Provo, United States

To better understand how human teams work together and how to work towards intuitive human-robot interaction, in this work we examine four sub-components of collaborative manipulation (co-manipulation), using motion and haptics. We define co-manipulation as a group of two or more agents collaboratively moving an object. We first define and examine a static or rest state to demonstrate a method of detecting transitions between the static state and an active state, where one or more agents are moving towards an intended goal. Second, we analyze a variety of signals during movements in each of the six rigid body degrees of freedom of the co-manipulated object. This data allows us to identify the best signals that correlate with the desired motion of the team for use in the development of future robotic controllers. Third, we examine the completion percentage of each task. The performance on those tasks is also used to determine which motion objectives can be communicated via haptic feedback to provide an idea of the relative difficulty of communicating each task. Finally, a metric is derived to determine if participants divide two degree-of-freedom tasks into separate degrees of freedom or if they take the most direct path. These four components contribute to the necessary groundwork for advancing intuitive human-robot interaction by improving our understanding of how human teams work together using motion and haptics.