Impact of Two Adjustable-Autonomy Models on the Scalability of Single-Human/Multiple-Robot Teams for Exploration Missions

A flexible adjustable autonomy model for robot-team supervision results in better performance than the classic, rigid one, in which the operator directly chooses the autonomy level, as he or she can directly act at the error level.