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tematic error inx could not be determined as of yet
but considering the flipped signs for almost all esti-
mates made by the iterative method, numeric insta-
bility is likely to contribute to the fragile nature of
the solvePnPclass.
5.SUMMARYANDOUTLOOK
In thisworkanovel framework fordockingamo-
bile robot using only vision-based sensors and algo-
rithms was developed. A CNN based object detector
yielded bounding boxes of logos with high accuracy
and confidence. Measurements of the logos were
taken and related in a coordinate system. The fam-
ily of solvePnP algorithms implemented in OpenCV
was used to estimate the camera pose using the de-
tector results and intrinsic parameters. All methods
consistently estimated wrong distances in one of the
directions,namely thex-axis. Followingpreliminary
experiments, changes were made, in particular the
coplanarity of the object points was removed and re-
calibration of the camera undertaken, and the same
experiments run again. Unfortunately the errors per-
sisted, although improvements regarding the scatter-
ness of the pose estimates could be made. Conse-
quently, no control commands were generated and
docking of the robot could not take place in this in-
stance. For future reference, it is important to note
the fragility of the solvePnP algorithms. The source
of the errors is unclear and while additional point
pairs could improve results regarding compactness,
it seemsunlikely theycouldalleviate the largeerrors
inpredicting thexcoordinates.
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Joint Austrian Computer Vision and Robotics Workshop 2020
- Title
- Joint Austrian Computer Vision and Robotics Workshop 2020
- Editor
- Graz University of Technology
- Location
- Graz
- Date
- 2020
- Language
- English
- License
- CC BY 4.0
- ISBN
- 978-3-85125-752-6
- Size
- 21.0 x 29.7 cm
- Pages
- 188
- Categories
- Informatik
- Technik