Characterizing Motion Prediction in Small Autonomous Swarms

Prior investigations of swarm robot control focus on optimizing communication and coordination between agents, with at most one human control scheme, or with discrete (rather than continuous) human control schemes. In these studies, focus tends to be on human-robot interactions, including human-machine gesture interfaces, human-machine interaction during conversation, or evaluation of higher-level mental states like comfort, happiness and cognitive load. While there is early work in human control of Unmanned Arial Vehicles (UAVs) and interface design, there are few systematic studies of how human operators perceive fundamental properties of small swarms of ground-based semi-autonomous robots. Therefore, the goal of this study is to better understand how humans perceive swarms of semi-autonomous agents across a range of conditions.