The Effect of Display Type on Operator Prediction of Future Swarm States

Abstract

Large teams of robots that operate collectively, whose behavior emerges from local interactions with neighbors, are known as swarms. While significant progress has been made improving the hardware, communication capabilities, and autonomous operation of these swarms, we still have much to learn about how human operators control and interact with them. This research is necessary if real world swarms are to be deployed in the future. The study presented here investigates different methods of displaying information about the swarm state to operators, and asks them to make predictions about the swarm’s future state. In the study, participants are shown swarms performing one of three different behaviors, and are asked to use the information available from the display to make their predictions. Results show that summarizing the swarm’s current state to just an average position and bounding ellipse allowed predictions as accurate as those made when full state information was shown. Furthermore, two leader-based methods were used, whereby the operators were shown only a small subset of the swarm. However, such display methods were inferior for prediction than either the summary center and ellipse or full information methods. With these results, and with participant feedback about the helpfulness of the four display types, we hope future studies can make more informed decision about interface design when it comes to the control of swarms.