Navigation Functionalities for an Autonomous UAV Helicopter
Navigation Functionalities for an Autonomous UAV Helicopter
Navigation Functionalities for an Autonomous UAV Helicopter
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A.3. PAPER III 105<br />
altitude [m]<br />
20<br />
18<br />
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2<br />
0<br />
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dist<strong>an</strong>ce to pattern [m]<br />
[mm]<br />
400<br />
350<br />
300<br />
250<br />
200<br />
150<br />
100<br />
50<br />
altitude [m]<br />
20<br />
18<br />
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8<br />
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dist<strong>an</strong>ce to pattern [m]<br />
Fig. 6. RMS error in horizontal (left) <strong>an</strong>d vertical position (right) from simulation.<br />
of 95 kg, including 30 kg available <strong>for</strong> payload. The vision navigation system<br />
consists of two PC104 stacks with PIII 700 MHz processors, the inertial<br />
sensors of the YAS, <strong>an</strong>d a single st<strong>an</strong>dard CCD camera with approx. 45<br />
degrees horizontal <strong>an</strong>gle of view which is mounted on <strong>an</strong> off-the-shelf p<strong>an</strong>/tilt<br />
unit (PTU). One of the two computers is dedicated to sensor m<strong>an</strong>agement<br />
<strong>an</strong>d low level control of the helicopter, the other one <strong>for</strong> image processing <strong>an</strong>d<br />
control of the camera <strong>an</strong>d the PTU. The two computers communicate over a<br />
RS232C serial link. They are built inside a shock <strong>an</strong>d vibration isolated box,<br />
which also includes a precision GPS, a barometric altitude sensor, a compass,<br />
a video recorder, a video tr<strong>an</strong>smitter, <strong>an</strong>d a wireless Ethernet bridge. The<br />
PTU is mech<strong>an</strong>ically limited to 111 degrees tilt <strong>an</strong>d ±180 degrees p<strong>an</strong>, the<br />
max. <strong>an</strong>gular rate is 300 degrees/s <strong>an</strong>d the resolution 0.051 degrees. It is<br />
mounted on a vibration isolating plat<strong>for</strong>m on the underside of the helicopter<br />
body.<br />
We estimated the RMS error of the vision system in position <strong>an</strong>d attitude<br />
depending on the relative position to the pattern in leveled flight. For<br />
each position 1000 samples were generated using a feature noise model that<br />
included noise from image <strong>for</strong>mation, digitization, <strong>an</strong>d segmentation. We developed<br />
a method to <strong>an</strong>alyze noise in ellipse center position <strong>an</strong>d semi-axis<br />
length. Errors introduced by the tr<strong>an</strong>s<strong>for</strong>mation from the camera frame into<br />
the body frame were not considered in simulation. Fig. 6 shows the RMS errors<br />
(1σ) in horizontal <strong>an</strong>d vertical position. The error doesn’t ch<strong>an</strong>ge much<br />
in the simulated envelope (a 20 m radius hemisphere, with a ”blind” sector<br />
from azimuth 0 to 15 degrees) due to different triplet sizes <strong>an</strong>d sub-pixel<br />
feature extraction. For pitch <strong>an</strong>d roll the error behaves similar to the horizontal<br />
error, with a maximum RMS value of ≈1 degree, the error in heading<br />
is negligible.<br />
The actual accuracy of the vision system was evaluated through <strong>an</strong> inflight<br />
comparison with a navigation solution based on the YAS <strong>an</strong>d a precision<br />
RTK GPS which supplied horizontal/vertical position with 10 mm/15 mm<br />
[mm]<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5