Teams for Teams Performance in Multi-Human/Multi-Robot Teams

Abstract

The present study addresses the interaction between automation and organization of human teams in controlling large robot teams performing an Urban Search and Rescue (USAR) task. We identify three subtasks: perceptual - visual search for victims, assistance - teleoperation to assist robot, and navigation - path planning and coordination. For the studies reported, navigation was selected for automation because it involves weak dependencies among robots making it more complex and because it was shown in an earlier experiment to be the most difficult. Two possible ways to organize operators were identified as assignment of robots to particular operators or as a shared pool in which operators service robots from the population as needed. The experiment compares two member teams of operators controlling teams of 12 robots each, in the assigned robots conditions or sharing control of 24 robots in the shared pool conditions using either waypoint control or autonomous path planning. Automating path planning improved system performance. Effects of team organization were equivocal.