[CapoCaccia - announce] IROS2019 Workshop

[Yulia Sandamirskaya]

Dear Neuromorphs,

I would like to invite you to attend the IROS-2019 Workshop 

“Cognitive Vehicles: Perception, learning and decision making under real-world constraints. Is bio-inspiration helpful?”

https://cogvehicles2019.github.io <https://cogvehicles2019.github.io/>

The topic of the workshop with its 11 invited talks is at the very core of themes that we have pursue in our Neuromorphic community:  what can be learn from biological neuronal and cognitive systems to make artificial cognition (or AI) more flexible, adaptive, agile and fit for the “real-world”, while also addressing the need for robustness, reproducibility, reliability, and safety of technological applications. 

The workshop will take place on 8. November 2019 as part of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) in Macau, China. It is far for most of us, but if you are going to IROS anyway, you don’t want to miss it! 

The workshop will be endorsed by the NEUROTECH CSA (https://neurotechai.eu) and European Society for Cognitive Systems EUCOG (https://neurotechai.eu).

All the information about the Workshop is also summarised in the attached flyer. Please, spread the word and contribute yourself to our discussions! 

>>>>> 


Workshop on Cognitive Vehicles:
Perception, learning and decision making under real-world constraints. Is bio-inspiration helpful?

November 8, 2019 - IEEE/RSJ International Conference on Intelligent Robots and Systems - Macau, China

Workshop Description

The goal of the workshop is to discuss potential benefits and pitfalls in applying bio- inspired approaches when developing intelligent real-world systems that perceive, interact, learn, and make decisions. We will focus on the application area of intelligent, “cognitive” vehicles. While biological inspiration has led to some of the most successful approaches in perception and machine learning in form of deep neural networks, their deployment in real-world, safety-critical settings is yet limited. We aim to explore and critically discuss what biological inspiration in perception, learning, and “cognition" could bring in the future for increasing intelligence of vehicles and other robotic systems. The workshop will stimulate discussion of the role of biological inspiration in the development of future AI systems in the context of real-world, safety-critical applications of robotic systems in environments shared with humans.

https://cogvehicles2019.github.io <https://cogvehicles2019.github.io/>
Call for Papers

We invite contributions in the form of extended abstracts (min. 2 pages, max. 4 pages) in IEEE paper format to be presented at the workshop as posters and/or demos. Please follow the authors guidelines <http://ras.papercept.net/conferences/support/support.php> and use the LaTex <http://ras.papercept.net/conferences/support/tex.php> or  <https://www.iros2019.org/>MS <http://ras.papercept.net/conferences/support/word.php> Word <http://ras.papercept.net/conferences/support/word.php> templates for the IROS conference <https://www.iros2019.org/>. Outstanding contributions will be selected for oral presentations.

We plan to publish extended versions of the papers accepted to the workshop as an article collection around the research topic of Towards Cognitive Vehicles: perception, learning and decision making under real-world constraints. Is bio- inspiration helpful? in Frontiers in Neurorobotics <https://www.frontiersin.org/journals/neurorobotics>. Additionally, accepted papers and eventual supplementary material will be made available on the workshop website.

Important Dates

Initial submission: 01.09.2019 Notification of acceptance: 10.09.2019 Camera-ready deadline: 20.09.2019 Workshop day: 08.11.2019

Submission

Please submit your contribution via EasyChair <https://easychair.org/account/signin_timeout?l=OfdOYPcZK0ckDHfSd0SEs5>.


Topics

Applications

-  Intelligent vehicles (cars, UAVs,...)

-  Human-machine interaction

-  Intelligence in the cockpit

Perception

-  Robust accountable and scalable perception with neural networks and without

-  Multi-modal perception and sensory integration

-  Attention and cognitive control in visual and tactile perception

-  Gesture recognition

-  Perception for action

Learning

-  Machine learning for vehicles

-  Fast inference and learning

-  Online learning and reliability

-  Embedded machine learning

-  Learning in complex hierarchical control systems

Cognitive Architectures

-  Cognitive architectures and machine learning / neuronal networks

-  Cognitive architectures for action selection

-  Scalable cognitive architectures

-  Learning cognitive architectures


Invited Speakers

Michael Würtenberger, BMW Group, Germany

Gustav Markkula, University of Leeds, United Kingdom

Michael Milford, Queensland University of Technology, Australia

Davide Scaramuzza, University of Zurich, Switzerland

Tansu Celikel, Radboud University Nijmegen, Netherlands

Dongheui Lee, Technial University of Munich, Germany

Yulia Sandamirskaya, UZH/ETH Zurich, Switzerland

Terrence C. Stewart, University of Waterloo, Canada

Gregor Schöner, Ruhr-Universität Bochum, Germany

Justus Piater, University of Innsbruck, Austria

Robert Haschke, University of Bielefeld, Germany 


Organisers

Florian Mirus: AI, Robotics, & Cognitive Systems; BMW Research, New Technologies, Innovations

Mohsen Kaboli: AI, Robotics, & Cognitive Systems; BMW Research, New Technologies, Innovations

Nicolai Waniek: Reinforcement Learning and Planning, Bosch Center for Artificial Intelligence (BCAI)
Jörg Conradt: Computational Science and Technology, KTH, Stockholm

Yulia Sandamirskaya: Institute of Neuroinformatics, UZH/ETH Zurich 
<<<<<<<<<<<<<<


Kind regards,

Yulia 

 


—
Dr. Yulia Sandamirskaya
Institute of Neuroinformatics (INI)
UZH / ETH Zurich
Winterthurerstrasse 190, 8057 Zurich
E-mail: ysandamirskaya at ini.uzh.ch <mailto:ysandamirskaya at ini.uzh.ch>
Tel: +41 44 63 53045
www.sandamirskaya.eu <http://www.sandamirskaya.eu/>
https://neurotechai.eu <https://neurotechai.eu/>
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