Autonomous Robots Journal Special Issue:
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Learning for Human-Robot Collaboration
Deadline: October 1st, 2016
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Once isolated behind safety fences, the new emerging generation of robots
endowed with more precise and sophisticated sensors, as well as better
actuators, are materializing the idea of having robots working alongside
people not only on manufacturing production lines, but also in spaces such
as houses, museums, and hospitals. In this context, one of the next
frontiers is the collaboration between humans and robots, which raises new
challenges for robotics. A collaborative robot must be able to assist
humans in a large diversity of tasks, understand its collaborator's
intentions as well as communicate its own, predict human actions to adapt
its behavior accordingly, and decide when it can lead the task or when just
follow its human counterpart. All these aspects demand the robot to be
endowed with an adaptation capability so that it can satisfactorily
collaborate with humans. In this sense, learning is a crucial feature for
creating robots that can execute different tasks, and rapidly adapt to its
human partner's actions and requirements.
The goal of this special issue is to document and highlight recent progress
in the use of machine learning for human-robot collaboration tasks. In
recent years, various interesting approaches and systems have been proposed
that tackle different aspects of human-robot collaboration. This journal
special issue will therefore present the state-of-the-art in the field and
discuss future challenges and research opportunities.
List of topics:
Papers addressing one or more of the topics below in the context of
human-robot collaboration are of particular interest:
* Learning from demonstration
* Reinforcement learning
* Active learning
* Force and impedance control
* Physical human-robot interaction
* Human-robot coordination
* Recognition and prediction of human actions
* Reactive and proactive behaviors
* Roles allocation
* Haptic communication
* Cooperative human-human interaction
* Human activity understanding
* Learning from tactile experiences
* Human-robot collaborative tasks in manufacturing
Important Dates:
* Paper submission deadline: October 1st, 2016
* Notification to authors: November 30th, 2016
* Final manuscript due: December 15th, 2016
* Final decision: January 10th, 2017
Guest editors:
Heni Ben Amor ([log in to unmask]) - Assistant Professor (Arizona State
University)
Leonel Rozo ([log in to unmask])- Senior postdoctoral fellow (Italian
Institute of Technology IIT)
Sylvain Calinon ([log in to unmask]) - Permanent Researcher (IDIAP
research institute)
Dongheui Lee ([log in to unmask]) - Assistant Professor (Technical University of
Munich)
Anca Dragan ([log in to unmask]) - Assistant Professor (UC Berkeley)
Submission:
Papers must be prepared in accordance with AURO guidelines.
All papers will be reviewed following the regular reviewing procedure of
the journal.
More information at:
http://static.springer.com/sgw/documents/1572468/application/pdf/AURO+CFP+-+Human-Robot+Collaboration.pdf
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Heni Ben Amor, PhD
Assistant Professor of Robotics
Interactive Robotics Lab
Arizona State University
Lab: http://lab.engineering.asu.edu/interactive-robotics/
Personal: http://henibenamor.weebly.com/
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