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Figure6.Visualizationof the results with the objectbeingplacedatdifferinganglesanddistances on theoptical axis
Figure7.Disparity imageof theobjectviewedbytheIntel
RealSense camera. Occlusions induced by the stereo vi-
sionsystemmakeitdifficult toaccuratelylocatethegrasp-
ingareadepicted inFigure 1.
theobject isbeingrotated. Figure7alsoshowsthat it
isdifficult todepict thegrabbingareaoftheobjectfor
creating a fitting template from the disparity image.
Having a poorly chosen template leads to points be-
ing incorporated into thePCAestimation thatarenot
actually part of the grabbing area and therefore lead
to unexpected results. Nevertheless, it can be con-
cluded that the anomalies are not induced by means
of the methodused forestimating thepose.
Figure6showstheresults formeasurements taken
withtheobjectbeingplacedatdifferentanglesonthe
optical axis. Refer to Figure 3 for a visual presenta-
tion of this process. The angle depicted in Figure 6
corresponds to angleα shown in Figure 3. The dis-
tance mark relates to the distances shown on the X-
axis labels of the graphs in Figure 6. The anomalies
again can be explained by the problems mentioned
before. Therightgraph inFigure6clearlyshows the
limits of the proposed approach, as the structure of Table2.Regions inwhichthealgorithmyieldsresultssuf-
ficientenoughfor the industrialgraspingusecaseathand.
Angle [°] Distance [cm]
+/-0
30
-75+/-10
+/-20
+/-10aroundcamera
30
-75+/-20aroundcamera
+/-30aroundcamera
theboxplotsover thegraphchanges in respect to the
other twographs.
Figure8showstheresults formeasurements taken
with the object being placed at different angles
around the camera. The angle depicted in Figure
8 corresponds to angle β shown in Figure 3. The
anomalies again can be explained by the problems
mentionedbefore.
The results showthat theusable region for this al-
gorithmcanbesummarizedwithTable2. Argument-
ing, that theanomaliescanbeeliminatedbyusingthe
enhancements already listed. Angles depicted with
the ”around camera” suffix correspond to the object
being rotatedaround thecamerawithangleα, asde-
picted inFigure3.
5.Conclusion
This work presented an approach to estimate the
pose of a known object by using the principal com-
ponent analysis. This resembles a first step to esti-
mateanobject’sposewith linear statisticalmethods.
The results showed that theapproach is sufficient for
the industrial usecaseathand, sinceamaximumde-
viation of 0.2 cm compared to the ground truth is
achieved, when anomalies are ignored. The results
also show the limitations of this approach. Anoma-
17
Joint Austrian Computer Vision and Robotics Workshop 2020
- Titel
- Joint Austrian Computer Vision and Robotics Workshop 2020
- Herausgeber
- Graz University of Technology
- Ort
- Graz
- Datum
- 2020
- Sprache
- englisch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-85125-752-6
- Abmessungen
- 21.0 x 29.7 cm
- Seiten
- 188
- Kategorien
- Informatik
- Technik