Partial camera automation in an unmanned air vehicle

The present study focused on an intelligent, semiautonomous, interface for a camera operator of a simulated unmanned air vehicle (UAV). This interface used system “knowledge” concerning UAV motion in order to assist a camera operator in tracking an object moving through the landscape below. The semiautomated system compensated for the translations of the UAV relative to the earth. This compensation was accompanied by the appropriate joystick movements ensuring tactile (haptic) feedback of these system interventions. The operator had to superimpose self-initiated joystick manipulations over these system-initiated joystick motions in order to track the motion of a target (a driving truck) relative to the terrain. Tracking data showed that subjects performed substantially better with the active system. Apparently, the subjects had no difficulty in maintaining control, i.e. “following” the active stick while superimposing self-initiated control movements over the system-interventions. Furthermore, tracking performance with an active interface was clearly superior relative to the passive system. The magnitude of this effect was equal to the effect of update-frequency (2-5 Hz) of the monitor image. The benefits of update frequency enhancement and semiautomated tracking were the greatest under difficult steering conditions. Mental workload scores indicated that, for the difficult tracking-dynamics condition, both semiautomation and update frequency increase resulted in less experienced mental effort. For the easier dynamics this effect was only seen for update frequency