Trajectory Generation for Effective Sensing

Unmanned aerial vehicles (UAVs) stand to play a significant role in envisioned sensing and information gathering missions. The scope of these mission scenarios is expanding to include those missions for which the sensor and carrier vehicle will be in close proximity to the surrounding environment. Consequently, several unique problems are introduced. First, coupling between the motion of the vehicle and the direction of sensor pointing has a significant effect on gathered data. Second, view characteristics of sensed objects will vary appreciably over the sensor field-of-view. Such variations affect data quality amongst these sensed objects. Third, close proximity to obstacles requires a trajectory planning method that adequately accounts for vehicle dynamics to insure safe navigation. This paper develops a trajectory planning strategy to effectively sense an environment at close range. A generalized measure of sensing effectiveness is formulated and utilized as a performance metric. A randomized motion planning scheme is then utilized to generate dynamically-feasible trajectories that maximize sensing effectiveness within such environments.