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awareness, motivating and introducing fundamental
concepts inaneasilycomprehensiblemanner(scope:
24 hours f2f, 20 hours online). Advanced modules
primarily focus on people who already have prior
knowledgeincomputerscience/mathematics,aiming
at enabling a deeper understanding of fundamental
concepts (scope: 36hours f2f, 50hoursonline).
Exemplary, the following gives an insight into the
Robotics Advancedmodule, which puts the focus
on a fundamental understanding of robotic arms and
mobile robots [7]. Preparatory online sessions pro-
vide the necessary basics in calculus, linear algebra
and Python programming. During the subsequent
f2f units, participants are given two concrete prob-
lems: 1) mathematical description/modelling of a
certainroboticarmandits trajectory;2) indoor local-
ization and navigation of a mobile robot; By work-
ing on these tasks, participants learn about the kine-
matical model (direct/inverse kinematics, homoge-
neous transformation, DOF/DOM, Jacobian) as well
as sensor fusion and state estimation (probabilistic
model, Bayesian and Kalman filter). Teaching tools
are paper+pencil exercises, simulators (Python) and
the TurtleBot 2 robotics platform. The module con-
cludeswith the final exam(certification).
Adetaileddescriptionofallmodulescanbefound
at [1] andon theprojectwebsite (edlris.eu).
4. ImplementationandEvaluation
In2019,19RoboticsandAItrainingcourseswere
conductedandevaluatedusingquantitativeandqual-
itative methods. In sum, 271 people participated,
whereas 66% also successfully completed the cer-
tification. The majority (76%) of participants were
trainers. A survey among participants was adminis-
tered prior and after each course (Likert scale, open-
ended questions). Summing up the results, 92%
stated that their expectations towards the training
were met and over 90% that the face-to-face (f2f)
units were essential for their learning success. On
the contrary, only 80% agreed that the online units
were sufficiently aligned with the f2f units1. Fur-
thermore, participants mentioned that the gaps (in
terms of complexity) between the Basic and Ad-
vanced modules are too large, making it hard for
young trainees to fully understand the complex, ad-
vanced topics. In addition to the survey, quantita-
tive pre- and post-tests at AI Basic trainings were
conducted using a questionnaire with 10 multiple-
1averagepercentageoverall 4 trainingmodules choice knowledge questions. Data analysis (paired
t-test) showed a statistically significant learning gain
(t(21)=18.086, p<.001). Further data analysis is
ongoing and more extensive pre-/post-test evalua-
tionswillbeconductedduringtheupcomingtraining
courses.
5.ConclusionsandFuturework
This paper presented the European Driving Li-
cense for Robots and Intelligent Systems (EDLRIS),
a training and certification system to teach people
fundamental concepts of Robotics and AI. The first
training courses have been implemented and evalu-
ated in Austria and Hungary in 2019, and, due to the
greatdemand, further trainingsandcertificationswill
beconductedin2020. Inordertogetabetterfounded
assertion regarding the success of the entire system,
a more extensive quantitative evaluation will be im-
plemented. Furthermore, contents and structure of
the trainingmoduleswillbeadaptedaccording to in-
sightsandlessons-learnedfromthefirst implementa-
tions.
Acknowledgements
This project is supported by the European Union
fundingprogrammeInterregV-AAT-HU2014-2020
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20
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