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does not reason over different diagnosis but only over the set
of components which may be faulty. The components which
may be the faulty need either to be observed more closely
or need to be repaired. Additionally, one cannot assume that
this component works properly with the information given
so far. Thus, this set is sufficient to decide which action to
execute.
The rule engine consists of a set of rulesRwhere each
rule r is a tuple comprising the following elements.
• A set posObs defining observations which should have
been made
• A set negObs defining observations which should not
have been made
• A set posPosAb which is a set of components which
should have been diagnosed as possibly faulty
• A set negPosAb which is a set of components which
should not have been diagnosed as possibly faulty
• α an action to execute.
Due to the use of the sets, one can simply perform the
reasoning by intersecting the sets to determine if the rule
should be triggered. As some observations, may be missing
one may face the problem that neitherobsresource∈Obs nor
¬obsresource ∈Obs holds, thus one cannot take a decision
if the observation of the resource is true or false. If one
would strictly perform the reasoning a rule may not triggered
because obsresource 6∈Obs holds although ¬obsresource 6∈
Obs holds. This is of special interest as not every observer
may state regularly which observations are true but only state
which observations are false. To deal with this problem we
trigger a rule if no contradicting information is observed.
This is achieved by the following simple procedure.
Trigger the rule if neither of the following holds.
• posObs ∩Obs 6= ∅, where posObs = {¬po|po ∈
posObs}
• negObs∩Obs 6=∅
• posPosAb ∩ PosAb 6= ∅, where posPosAb =
{¬posAb|posAb∈posPosAb}
• negPosAb∩PosAb 6=∅
As only set operations are performed one can perform
an efficient reasoning which allows a fast reaction. Espe-
cially as one can assume that the sets posObs, negObs,
posPosAb andnegPosAb are small. Thus, one can perform
this checks inO(|posObs|∗log(Obs)+|negObs|∗log(Obs)+
|posPosAb|∗log(PosAb)+|negPosAb|∗log(PosAb))which
allows a fast reaction even in case of many observations or
many possible faulty components.
As rules, should only be used to allow the robot to react
to faults, instead of continuously checking the rules, they
are only checked if the set of observations or possible faulty
components changes. This allows to save resources but also
prohibits to trigger a rule multiple times without any change
in the system.
After deciding that a rule should be triggered one needs
to execute the action αwhich is defined for this rule. The
actions range from printing a message to the console or to a
log file over changing parameters to triggering the execution of an external script. Thus, one can trigger nearly arbitrary
behavior to react to a fault.
VI. USE CASE
Before we discuss related research, we will show a simple
use case of the system. The use case is the simplified
odometry calculation of a robot which delivery good in a
warehouse, see [10] for a detailed description of the robot.
The odometry is calculated using the wheel encoders and an
IMU is used to improve this odometry. The IMU is fused
with the calculation by using the rotation of the IMU instead
of the calculated rotation. Thus, if the IMU is fault free the
odometry is improved. To show the impact of the proposed
system three faults is simulated. The IMU can either be stuck
to zero after some time, it can overestimate the rotation by
20% or issue that there is no rotation after rotating a certain
amount of time.
To evaluate the impact of the system the robot was
commanded to move between six waypoints in the environ-
ment, for three minutes. During the movement, the wheel
encoder the IMU measurements and the real position of the
robot were determined. The real position of the robot was
determined with the help of an OptiTrack system. After the
movement of the robot was recorded the odometry is calcu-
lated using the wheel encoders and the IMU. Additionally,
one observer is used which checks if the calculated rotation
of the wheel encoder and the IMU correlate. This allows
detecting a fault of the IMU. Using this fault detection, the
diagnosis can calculate that the IMU is faulty. In such a case
the rule engine changes a parameter to ensure that the IMU
is no longer used for the odometry calculation.
The evaluation compares the error between the ground
truth and the calculated odometry which always uses the
IMU and the calculated odometry which only use the IMU
if it is not diagnosed to be faulty. In case the IMU was stuck
to zero after several seconds the mean error was reduced by
28.1% and the root mean squared error (RMS) was reduced
by 39.9%. In case the IMU was overestimating the rotation
by 20% the mean error was reduced by 25.6% and the root
mean squared error (RMS) was reduced by 35.6%. In case
the IMU was reporting zero rotation after one second of
rotation the mean error was reduced by 39.3% and the root
mean squared error (RMS) was reduced by 50.9%. Thus, the
use of the diagnosis system could react quickly enough to
improve the odometry calculation drastically. The evaluation
was performed on an intel i5-2430M with 8 GB of RAM
and took less than 2 % of the CPU.
VII. RELATED RESEARCH
We begin our discussion of related research with the
method proposed in [11]. The method adds to each software
module so-called software sensors. These sensors supervise
the execution of a software component which is treated as
a black box. Thus, the software component can be devel-
oped and tested independently from the sensors. During the
execution, the software sensor checks for faults and report
these faults on a diagnosis port. To ease the reuse of the
13
Proceedings of the OAGM&ARW Joint Workshop
Vision, Automation and Robotics
- Titel
- Proceedings of the OAGM&ARW Joint Workshop
- Untertitel
- Vision, Automation and Robotics
- Autoren
- Peter M. Roth
- Markus Vincze
- Wilfried Kubinger
- Andreas Müller
- Bernhard Blaschitz
- Svorad Stolc
- Verlag
- Verlag der Technischen Universität Graz
- Ort
- Wien
- Datum
- 2017
- Sprache
- englisch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-85125-524-9
- Abmessungen
- 21.0 x 29.7 cm
- Seiten
- 188
- Schlagwörter
- Tagungsband
- Kategorien
- International
- Tagungsbände