The remote manual teleoperation of an unmanned aerial vehicle (UAV) by a human operator creates a human-in-the loop system that is of great concern. In a remote teleoperation task, a human pilot must make control decisions based upon sensory information provided by the governed system. Often, this information consists of limited visual feedback provided by onboard cameras that do not provide an operator with an accurate portrayal of their immediate surroundings compromising the safety of the mobile robot. Due to this shortfall, haptic force feedback is often provided to the human in an effort to increase their perceptual awareness of the surrounding world. To investigate the effects of this additional sensory information provided to the human op-erator, we consider two haptic force feedback strategies. They were designed to provide either an attractive force to influence control behavior towards a reference trajectory along a flight path, or a repulsive force directing operators away from obstacles to prevent collision. Subject tests were con-ducted where human operators manually operated a remote UAV through a corridor environment under the conditions of the two strategies. For comparison, the conditions of no haptic feedback and the liner combination of both attractive and repulsive strategies were included in the study. Experi-mental results dictate that haptic force feedback in general (including both attractive and repulsive force feedback) improves the average distance from surrounding obstacles up to 21%. Further statis-tical comparison of repulsive and attractive feedback modalities reveal that even though a repulsive strategy is based directly on obstacles, an attractive strategy towards a reference trajectory is more suitable across all performance metrics. To further examine the effects of haptic aides in a UAV teleoperation task, the behavior of the human system as part of the control loop was also investigated. Through a novel device placed on the end effector of the haptic device, human-haptic interaction forces were captured and further analyzed. With this information, system identification techniques were carried out to determine the plausibility of deriving a human control model for the system. By defining lateral motion as a one-dimensional compensatory tracking task the results show that general human control behavior can be identified where lead compensation in invoked to counteract second-order UAV dynamics
