We are developing an architecture for controlling robot teams based on considering how control difficulty for different tasks grows with increases in team size. Our analysis suggests that assignments of persons to commander (single commands to entire robot team), operator (commands to individual robots), and coordinator (control of interdependent robots) roles can lead to the most efficient organization. The ability to assign tasks within or between operators makes scheduling these interactions an important factor in team performance. Two possible ways to organize operators are through Individual Assignments of robots or as a Call Center in which operators service robots from the population as needed. In recent experiments we have found that participants performing an Urban Search And Rescue (USAR) foraging task using waypoint control were at or over their limits when controlling 12 robots. The present study uses the same robots, environment, and level of autonomy but with teams of two operators assigned to control 24 robots. These operators controlled teams of 12 robots in the Individual Assignment condition. In the Call Center condition operators shared control of the 24 robots. For this task and level of robot autonomy Individual Assignment participants performed marginally better searching larger regions but without finding more victims.
['Huadong Wang', 'Shih Yi Chien', 'Michael Lewis', 'Prasanna Velagapudi', 'Paul Scerri', 'Katia P. Sycara']
Human teams for large scale multirobot control