(Georgia Institute of Technology, 2005-09)
Wu, Allen D.; Johnson, Eric N.; Proctor, Alison A.
Many onboard navigation systems use the Global Positioning System to bound the errors
that result from integrating inertial sensors over time. Global Positioning System information,
however, is not always accessible since it relies on external satellite signals. To this
end, a vision sensor is explored as an alternative for inertial navigation in the context of an
Extended Kalman Filter used in the closed-loop control of an unmanned aerial vehicle. The
filter employs an onboard image processor that uses camera images to provide information
about the size and position of a known target, thereby allowing the flight computer to derive
the target's pose. Assuming that the position and orientation of the target are known a priori,
vehicle position and attitude can be determined from the fusion of this information with inertial
and heading measurements. Simulation and flight test results verify filter performance
in the closed-loop control of an unmanned rotorcraft.