Two of our works have been accepted as full papers for presentation and publication in the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2016).

“Postures of a Robot Arm – window to robot intentions?” authored by my doctoral student Sridatta Chaterjee and co-authored by my colleagues Drs. Oren Shriki and Idit Shalev.

Abstract— Body language of robot arms, have rarely been explored as a medium of conveying robot intentions. An exploratory study was done focusing on two questions: one, if robot arm postures can convey robot intentions, and two, if participants coming in contact with this robot arm for the first time can associate any meaning to the postures without watching the robot in action, or working with it. Thirty five participants of a wide age range (25-70) took part in this exploratory study. Results show that participants could interpret some postures. Four distinct types of postures have been selected to four separate categories by the majority of participants irrespective of their age. In addition, postures selected in categories like, ‘Robot giving object in a friendly manner’; ‘Robot is saying Hi!’, ‘Robot has been told not to disturb’ show similarity to body language exhibited by humans and animals while communicating such messages.

Posture 8, what is the robot doing?

“The Influence of Following Angle on Performance Metrics of a Human-Following Robot” co-authored by our graduate students Shanee Honig and Dror Katz, and my colleague Prof. Yael Edan.

Abstract— Robots that operate alongside people need to be able to move in socially acceptable ways. As a step toward this goal, we study how and under which circumstances the angle at which a robot follows a person may affect the human experience and robot tracking performance. In this paper, we aimed to assess three following angles (0◦ angle, 30◦ angle, and 60◦ angle) under two conditions: when the robot was carrying a valuable personal item or not. Objective and subjective indicators of the quality of following and participants’ perceptions and preferences were collected. Results indicated that the personal item manipulation increased awareness to the quality of the following and the following angles. Without the manipulation, participants were indifferent to the behavior of the robot. Our following algorithm was successful for tracking at a 0◦ and 30◦ angle, yet it must be improved for wider angles. Further research is required to obtain better understanding of following angle preferences for varying environment and task conditions.

Following angles of a person-following robot: straight from behind or wider angles?

NY, Looking forward to two great presentations!