<html>
<head>
<meta http-equiv="content-type" content="text/html; charset=utf-8">
</head>
<body bgcolor="#FFFFFF" text="#000000">
<p>[Apologies for cross-posting]<br>
</p>
<p>Dear colleagues,
<br>
<br>
We are pleased to announce the Call for Papers of the AURO special
Issue on "Learning for Human-Robot Collaboration". Please see all
the details below.
<br>
<br>
<br>
<i>Autonomous Robots Journal</i> Special Issue:
<br>
<br>
<b>Learning for Human-Robot Collaboration</b>
<br>
Deadline: <u>November 30th, 2016</u>
<br>
<br>
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.
<br>
<br>
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.
<br>
<br>
List of topics:
<br>
Papers addressing one or more of the topics below in the context
of human-robot collaboration are of particular interest:
<br>
<br>
* Learning from demonstration
<br>
* Reinforcement learning
<br>
* Active learning
<br>
* Force and impedance control
<br>
* Physical human-robot interaction
<br>
* Human-robot coordination
<br>
* Recognition and prediction of human actions
<br>
* Reactive and proactive behaviors
<br>
* Roles allocation
<br>
* Haptic communication
<br>
* Cooperative human-human interaction
<br>
* Human activity understanding
<br>
* Learning from tactile experiences
<br>
* Human-robot collaborative tasks in manufacturing
<br>
<br>
Important Dates:
<br>
* Paper submission deadline: November 30th, 2016
<br>
* Notification to authors: January 15, 2017
<br>
* Final manuscript due: February 1st, 2017
<br>
* Final decision: February 15th, 2017
<br>
<br>
Guest editors:
<br>
Heni Ben Amor (<a class="moz-txt-link-abbreviated"
href="mailto:hbenamor@asu.edu">hbenamor@asu.edu</a>) - Assistant
Professor (Arizona State University)
<br>
Leonel Rozo (<a class="moz-txt-link-abbreviated"
href="mailto:leonel.rozo@iit.it">leonel.rozo@iit.it</a>) -
Senior postdoctoral fellow (Italian Institute of Technology IIT)
<br>
Sylvain Calinon (<a class="moz-txt-link-abbreviated"
href="mailto:sylvain.calinon@idiap.ch">sylvain.calinon@idiap.ch</a>)
- Permanent Researcher (IDIAP research institute)
<br>
Dongheui Lee (<a class="moz-txt-link-abbreviated"
href="mailto:dhlee@tum.de">dhlee@tum.de</a>) - Assistant
Professor (Technical University of Munich)
<br>
Anca Dragan (<a class="moz-txt-link-abbreviated"
href="mailto:anca@berkeley.edu">anca@berkeley.edu</a>) -
Assistant Professor (UC Berkeley)
<br>
<br>
Submission:
<br>
Papers must be prepared in accordance with AURO guidelines.
<br>
All papers will be reviewed following the regular reviewing
procedure of the journal.
<br>
<br>
More information at: <br>
</p>
<p><a class="moz-txt-link-freetext"
href="http://static.springer.com/sgw/documents/1572468/application/pdf/AURO+CFP+-+Human-Robot+Collaboration.pdf">http://static.springer.com/sgw/documents/1576377/application/pdf/AURO+CFP+-+Human-Robot+Collaboration.pdf<br>
</a></p>
<br>
<pre class="moz-signature" cols="72">--
Leonel Rozo,
Senior postdoctoral researcher
Advanced Robotics Department
Istituto Italiano di Tecnologia (IIT)
<a class="moz-txt-link-freetext" href="http://leonelrozo.weebly.com/">http://leonelrozo.weebly.com/</a></pre>
</body>
</html>