Human-controlled robots are utilized in many situations and such use is becoming widespread. This thesis details research that allows a single human to interact with a team of robots performing tasks that require cooperation. The research provides insight into effective interaction design methods and appropriate interface techniques. The use of team-level autonomy is shown to decrease human workload while simultaneously improving individual robot efficiency and robot-team cooperation. An indoor human-robot interaction testbed was developed at the BYU MAGICC Lab to facilitate experimentation. The testbed consists of eight robots equipped with wireless modems, a field on which the robots move, an overhead camera and image processing software which tracks robot position and heading, a simulator which allows development and testing without hardware utilization and a graphical user interface which enables human control of either simulated or hardware robots. The image processing system was essential for effective robot hardware operation and is described in detail. The system produced accurate robot position and heading information 30 times per second for a maximum of 12 robots, was relatively insensitive to lighting conditions and was easily reconfigurable. The completed testbed was utilized to create a game for testing human-robot interaction schemes. The game required a human controlling three robots to find and tag three robot opponents in a maze. Finding an opponent could be accomplished by individual robots, but tagging an opponent required cooperation between at least two robots. The game was played by 11 subjects in five different autonomy modes ranging from limited robot autonomy to advanced individual autonomy with basic team-level autonomy. Participants were interrupted during the game by a secondary spatial reasoning task which prevented them from interacting with the robots for short periods of time. Robot performance during that interruption provided a measure of both individual and team neglect tolerance. Individual robot neglect tolerance and performance did not directly correspond to those quantities at the team level. The interaction mode with the highest levels of individual and team autonomy was most effective; it minimized game time and human workload and maximized team neglect tolerance.
College and Department
Ira A. Fulton College of Engineering and Technology; Mechanical Engineering
BYU ScholarsArchive Citation
Anderson, Jeffrey D., "Methods and Metrics for Human Control of Multi-Robot Teams" (2006). Theses and Dissertations. 820.
robot, robot teams, robot team, human robot interaction, adjustable autonomy, robot control interface, computer vision, metrics, graphical user interface, GUI, MAGICC