[robotics-worldwide] [journals] AURO Special Issue: Learning for Human-Robot Collaboration (Deadline Extension)

Heni Ben Amor hbenamor at asu.edu
Mon Nov 28 22:33:53 PST 2016

Autonomous Robots Journal Special Issue:

Learning for Human-Robot Collaboration
NEW DEADLINE: December 31st, 2016

By popular demand from the community, the deadline has been extended to
December 31st, 2016. There will be no further extension after that.

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: December 31st, 2016
* Notification to authors: March 1st, 2017
* Final manuscript due: March 16th, 2017
* Final decision: April 10th, 2017

Guest editors:
Heni Ben Amor (hbenamor at asu.edu) - Assistant Professor (Arizona State
Leonel Rozo (leonel.rozo at iit.it)- Senior postdoctoral fellow (Italian
Institute of Technology IIT)
Sylvain Calinon (sylvain.calinon at idiap.ch) - Permanent Researcher (IDIAP
research institute)
Dongheui Lee (dhlee at tum.de) - Assistant Professor (Technical University of
Anca Dragan (anca at berkeley.edu) - Assistant Professor (UC Berkeley)

Papers must be prepared in accordance with AURO guidelines.
All papers will be reviewed following the regular reviewing procedure of
the journal.

Heni Ben Amor, PhD
Assistant Professor of Robotics
Interactive Robotics Lab
Arizona State University
Lab: https://urldefense.proofpoint.com/v2/url?u=http-3A__lab.engineering.asu.edu_interactive-2Drobotics_&d=DgIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=nwAcpxRC14RtFJnex-LKFckZa2noG0OKk4mK9TQELG8&s=9SJPpLz4xKRC9DCR_if4DTXg2h8s2NmBoUCL_AAZNZ8&e= 
Personal: https://urldefense.proofpoint.com/v2/url?u=http-3A__henibenamor.weebly.com_&d=DgIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=nwAcpxRC14RtFJnex-LKFckZa2noG0OKk4mK9TQELG8&s=C-xT74CSBa1e7i7muUV6KD0sE9YgesvxKqny2olAVx8&e= 

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