In this paper, the development of a vision based system for a small-scale VTOL-MAV is presented. The on-board
GPS/INS navigation system is augmented by further sensors in order to allow for an autonomous waypoint mode.
Especially in urban environments the GPSsignal quality is disturbed by shading and multipath propagation.
The investigated vision system based on algorithms analyzing the optical flow is essential to enable the helicopter
to reliably hover even in these scenarios. Due to the integration of the vision based navigation information into
the navigation filter, GPSsignal outages can be bridged. The necessary height above ground information is
estimated from the relative altitude change given by the barometric altimeter and the optical flow.
A method for precise geo-location of objects that are observed by an airborne camera is described in this paper.
The platform for image acquisition is a micro aerial vehicle (MAV) with an integrated navigation system. From
the captured image sequences and MAV navigation data, the three-dimensional positions of objects of interest
are retrieved. Different techniques for image feature tracking are compared. Combining measurements from
multiple viewpoints in a Bundle Adjustment process yields optimal accuracy of the estimated object positions.
The robustness of the optimization is enhanced by tight integration of data from both the vision and the navigation system.
This paper focusses on the automated detection and tracking of moving objects in a camera sequence, that
is provided by a small, electrically powered four-rotor helicopter in a hover-and-stare scenario. Two different
algorithms for identifying independently moving areas are investigated and compared. The first approach bases
on the previous compensation of the camera movement by estimation of homographies. Moving regions are
extracted by robust background subtraction. The second approach bases on a dense optical flow field and needs
no stabilization: Single points are identified that move not consistently with the background plane. These points
are merged into objects by a cluster analysis algorithm. Furthermore, a strategy for tracking these objects over
time is described including a Kalman filter. Due to several reasons, not every extracted area corresponds to
an independently moving object and a heuristic rule set is used to sort artifacts out. Experimental results on
in-flight images are presented and the performances of the developed algorithms are compared. Finally, first
steps towards a geographic location of the tracked objects are described.
Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is
capable of flying automatically on a predefined path the range of possible applications is widened significantly.
This paper addresses the development of the integrated GPS/INS/MAG navigation system and a waypoint
navigator for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off
weight below 1 kg. The core of the navigation system consists of low cost inertial sensors which are continuously
aided with GPS, magnetometer compass, and a barometric height information. Due to the fact, that the yaw
angle becomes unobservable during hovering flight, the integration with a magnetic compass is mandatory.
This integration must be robust with respect to errors caused by the terrestrial magnetic field deviation and
interferences from surrounding electronic devices as well as ferrite metals. The described integration concept
with a Kalman filter overcomes the problem that erroneous magnetic measurements yield to an attitude error
in the roll and pitch axis. The algorithm provides long-term stable navigation information even during GPS
outages which is mandatory for the flight control of the UAV.
In the second part of the paper the guidance algorithms are discussed in detail. These algorithms allow the
UAV to operate in a semi-autonomous mode <b>position hold</b> as well an complete autonomous <b>waypoint mode</b>.
In the position hold mode the helicopter maintains its position regardless of wind disturbances which ease the
pilot job during hold-and-stare missions. The autonomous waypoint navigator enable the flight outside the range
of vision and beyond the range of the radio link. Flight test results of the implemented modes of operation are