[robotics-worldwide] [journals] 2nd CFP: Advanced Robotics Special Issue on Machine Learning and Data Engineering in Robotics

Komei Sugiura komei.sugiura at nict.go.jp
Fri May 15 04:14:04 PDT 2015

# Apologies for multiple copies

 Call for papers: Advanced Robotics
 Special Issue on "Machine Learning and Data Engineering in Robotics"

 Paper Submission Deadline: June 30, 2015
 Publication in Vol. 30, No. 9 (May 2016)

With the growth of sensor data and networked devices, machine learning
has been gaining interest both in robotics and many other disciplines.
The collaboration between machine learning and data engineering in
robotics could have a strong impact on the way robots or services help
our lives as well as on deepening our understanding of human intelligence.

This special issue attempts to showcase state-of-the-art studies ranging
from sensor data management through learning real-world data or
behaviors as well as probabilistic models in constructive approaches.
Emphasis will be given to novel algorithms and theories in the field,
quantitatively comparable research results, robotic applications that
help people, and constructive approaches that model human cognitive skills.

We solicit original and high-quality papers on machine learning and data
engineering in robotics. We also solicit survey papers that discuss open
challenges and state-of-the-art techniques. Topics of interest include,
but are not limited to:

- Probabilistic models and reasoning
- Neural networks
- Data compression
- Feature description
- Sensor fusion
- Multimodal learning/interaction
- Robot dialogue
- Scene understanding
- Generic object recognition
- Symbol grounding
- Symbol emergence in robotics
- Language acquisition
- Reinforcement learning
- Imitation learning
- Motion recognition
- Cyber-physical systems
- Big data
- Cloud robotics
- Service robots

Submission:   Your complete manuscript (either PDF file or MS word file)
should be submitted by June 30, 2015 to the office of Advanced Robotics,
the Robotics Society of Japan through our homepage
(http://www.rsj.or.jp/advanced_e/submission). Instruction to the authors
and the sample formats of the manuscript are also available there.
Please send another copy to Dr. Komei Sugiura (komei.sugiura at nict.go.jp)
as well for the confirmation.

Guest Co-Editors:
 Prof. Sven Behnke (University of Bonn, Germany)
 Prof. Dana Kulic (University of Waterloo, Canada)
 Prof. Kimitoshi Yamazaki (Shinshu University, Japan)
 Dr. Komei Sugiura (NICT, Japan)

 Komei Sugiura, Ph.D.
 Senior Researcher,
 National Institute of Information and Communications Technology

 3-5 Hikaridai, Seika, Soraku, Kyoto 619-0289, Japan
 Email: komei.sugiura at nict.go.jp
 URL:   http://komeisugiura.jp/index_en.html

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