  In human-robot collaborative interaction scenarios, nonverbal communication
plays an important role. Both, signals sent by a human collaborator need to be
identified and interpreted by the robotic system, and the signals sent by the
robot need to be identified and interpreted by the human. In this paper, we
focus on the latter. We implemented on an industrial robot in a VR environment
nonverbal behavior signalling the user that it is now their turn to proceed
with a pick-and-place task. The signals were presented in four different test
conditions: no signal, robot arm gesture, light signal, combination of robot
arm gesture and light signal. Test conditions were presented to the
participants in two rounds. The qualitative analysis was conducted with focus
on (i) potential signals in human behaviour indicating why some participants
immediately took over from the robot whereas others needed more time to
explore, (ii) human reactions after the nonverbal signal of the robot, and
(iii) whether participants showed different behaviours in the different test
conditions. We could not identify potential signals why some participants were
immediately successful and others not. There was a bandwidth of behaviors after
the robot stopped working, e.g. participants rearranged the objects, looked at
the robot or the object, or gestured the robot to proceed. We found evidence
that robot deictic gestures were helpful for the human to correctly interpret
what to do next. Moreover, there was a strong tendency that humans interpreted
the light signal projected on the robot's gripper as a request to give the
object in focus to the robot. Whereas a robot's pointing gesture at the object
was a strong trigger for the humans to look at the object.
