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Unmanned aerial vehicles (UAVs) stand to play a significant role in future 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, such as in urban operations. Several unique problems related to guidance, navigation and control are introduced that separate these tasks from the existing paradigm for information gathering missions at standoff range. This paper examines the challenges related to autonomous sensor planning missions in these close proximity environments and discusses solution strategies to achieve maximal sensing effectiveness. Specifically, results from vision-based navigation research are discussed and the concept of a geometric sensing effectiveness criterion is introduced and subsequently utilized for motion planning.

Missions envisioned for micro air vehicles may require a high degree of autonomy to operate in unknown environments. As such, vision is a critical technology for mission capability. This paper discusses an autopilot that uses vision coupled with GPS and altitude sensors. One use of vision processing analyzes a horizon to estimate roll and pitch information. Another use tracks a feature point to estimate position relative to a target. This paper presents examples of waypoint navigation and homing using vision-based feedback. The examples indicate the vision provides sufficient information to achieve the missions.