![](bg8.png)
Figure 9 illustrates the progress of the downforce
value F and its point of action
~
P
F
. It can be seen
that the resulting values are very realistic: The to-
tal amount of downforce F is reduced from desired
2 200 N to 1 760 N and the x position of the point of
action (P
F
x
) moves about 8 cm below the robot center.
Figure 10: Real climbing robot CROMSCI navigating on a
concrete wall.
In the latest history, the simulation system has
e. g. been used to validate safety measures and risk
prediction methods (Schmidt, 2013) or to perform a
foresighted analysis of the terrain. The accuracy of
the thermodynamic model of the vacuum system it-
self has been proven in earlier experiments (Wettach
et al., 2005). The complete simulation framework
is accurate enough to optimize the control software
in the simulation, so that only some fine-tuning is
needed to apply these algorithms on the real machine
depicted in figure 10. Some demonstration videos
8
of CROMSCI in operation prove this transferability of
control algorithms from simulation to reality.
7 CONCLUSIONS
This paper presented a novel framework on the ba-
sis of SIMVIS3D for simulating a climbing robot
using negative pressure adhesion and an omnidirec-
tional drive system. It could be shown that the system
is able to simulate the airflows and pressure changes
of a complex vacuum system with seven suction cups
and one reservoir. The structure of the ground has a
direct impact on the leakage values in order to model
different surface characteristics. Hence, this tool fa-
cilitates the development of control algorithms inde-
pendent of the real robot and enables an offline and
realtime validation in arbitrary 3D environments.
Further work will focus on a porting to FINROC
9
and an easier handling of the physical simulation,
8
http://agrosy.cs.uni-kl.de/en/galerie/
cromsci-medien/
9
http://www.finroc.org
since the Blender export of collision objects does not
include joints. Additionally, a new robot prototype is
under construction: Its control software will be opti-
mized using this tool first, before executing and fine-
tuning it on the real system.
ACKNOWLEDGEMENTS
This research was funded by the German Bundesmin-
isterium f
¨
ur Wirtschaft und Technologie (BMWi), Zen-
trales Innovationsprogramm Mittelstand (ZIM).
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