IEEE TCDS Special Issue on Adaptive Personal Robot Interaction- Call for Papers Deadline

On 30 Sep, 2017

At IEEE - Piscataway, NJ USA 445 Hoes Lane, Piscataway Township, NJ 08854, USA

Categories: Deadlines, RAS Publications

Save to calendar


CFP: IEEE TCDS Special Issue on Adaptive Personal Robot Interaction

IEEE Transactions on Cognitive and Developmental Systems
Special Issue on Adaptive Personal Robot Interaction

AIM AND SCOPE

Personal robots have become a highlight in both research community and industry. They are expected to interact with humans at various scenarios, bring added value, or even to be respected and loved by humans. These expectations pose serious challenges to the capability of robots to interact with humans in a natural manner, especially in terms of cognition. Interactions could span from information-oriented and task-oriented interaction, to emotional interaction, and even social interaction. Robots will accomplish daily tasks when interacting with humans, like personal assistance, child education, or senior care, independently or collaboratively. It’s not easy to provide a fixed definition and scope to any of these tasks, or to program them in advance. Moreover, there is a lot of work to do in service personalization in order to meet the special needs of a user. Therefore, robots need to learn continuously and adapt/develop their capabilities based on their long-term interaction with users. Many research questions arise and wait for answers before this vision becomes a reality. Below are a few examples:

  • What are the special requirements for adaptive personal robot interaction?
  • What kind of theory framework is needed for adaptive personal robot interaction?
  • How can personal robots learn from humans continuously and develop/adapt their social interaction skills?
  • How to adapt multi-modal perception to make them more robust when working over time?
  • How to build trust and respect while interacting with humans? What’s the internal model of personal robot to adapt and evaluate the progress?
All these questions present serious challenges which call for a cross-disciplinary approach involving perception and cognition system, developmental robotics, computer vision, speech/NLP, multi-modality HRI (Human-Robot Interaction), personalization of robot service, innovation applications, psychology, user experience, and sensors/computing platforms. In the past, personal robots was not a mainstream application area, so researchers didn’t frequently communicate and collaborate with each other. However, given the clear demand of personal robots and the acceleration of technology development in related areas, such as robotics, computer vision and machine learning, personal robots can be equipped with more advanced interaction capabilities. It’s a great time now to make collective efforts to attack the challenges underlying adaptive personal robot interaction. Cross-disciplinary collaboration and innovation are deemed to be vital to the success of adaptive personal robot interaction. In addition, a systematic approach, targeting at real challenges in personal robot application, is important. It’s different from the longer-term approach that was applied in such areas as developmental robotics and emphasizes learning from scratch. Instead, it’s believed that the leverage of existing advances in computer perception is important to the achievement of realistic solutions. Finally, it’s believed that new solutions should consider efficient computing platforms, so that such solutions can demonstrate good feasibility in personal robots.

THEMES

This special issue aims to report state-of-the-art approaches and recent advances in adaptive personal robot interaction with a cross-disciplinary perspective, including theory foundation, machine learning and knowledge acquisition, adaptive perception/cognition sub-systems like computer vision. Topics relevant to this special issue include but are not limited to:

  • Theory framework for adaptive personal robot interaction
  • Machine learning algorithms for adaptive interaction
  • Adaptive learning for social interaction
  • Adaptive computer vision
  • Adaptive multi-modal perception/cognition, including multi-modal emotion recognition etc.
  • Adaptive psychology-based emotion engine
  • Efficient computing platform for adaptive personal robot interaction

SUBMISSION

Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://cis.ieee.org/publications.html. Submissions should be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee and please select the category “SI: Adaptive Human Robot Interaction”.

IMPORTANT DATES

30 September 2017 – Extended deadline for manuscript submission 
30 July 2017 – Deadline for manuscript submission 
15 Oct 2017 – Notification of authors
15 November 2017 – Deadline for revised manuscripts
15 December 2017 – Final version
For further information, please contact one of the following Guest Editors

GUEST EDITORS

Dr. Jiqiang SONG
Intel Labs China, Beijing, China
This email address is being protected from spambots. You need JavaScript enabled to view it.

Dr. Yimin ZHANG
Intel Labs China, Beijing, China
This email address is being protected from spambots. You need JavaScript enabled to view it.

Prof. Xiaoping CHEN
Department of Computer Science, University of Science and Technology of China, Hefei, China
This email address is being protected from spambots. You need JavaScript enabled to view it.

Dr. Takayuki KANDA
Intelligent Robotics and Communication Laboratory, ATR (Advanced Telecommunications Research Institute International), Kyoto, Japan
This email address is being protected from spambots. You need JavaScript enabled to view it.



2017-09-30 00:00:00
-0001-11-30 00:00:00

Easy Links