[robotics-worldwide] CFP: International Journal of Social Robotics - Special Issue on "Expectations, Intentions, and Actions"

Marc Hanheide m.hanheide at cs.bham.ac.uk
Thu Feb 24 02:28:21 PST 2011


[our apologies for cross-posting]

Dear colleagues,

please consider submitting your latest resarch results to the 
International Journal of Social Robotics - Special Issue on 
"Expectations, Intentions, and Actions"

=======================================================================
Website: http://www.dfki.de/~zender/soro-iea/
for questions, please contact: mlohse at techfak.uni-bielefeld.de
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IMPORTANT DATES:
Paper submission deadline: 	15 April 2011
Notification of acceptance: 	1 July 2011
Submission of final papers: 	1 September 2011
Final acceptance: 		1 November 2011
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Human-robot interaction is becoming increasingly complex through the
growing number of abilities, both cognitive and physical, available to
today's robots. At the same time, interaction is still often difficult
because the users do not understand the robots' internal states,
intentions, actions, and expectations. Vice versa, robots lack
understanding of the users' expectations, intentions, social signals,
and actions. Different robotic systems have been built and many studies
have been conducted unveiling the importance of properly designed
adaptive human-robot interaction strategies in general and appropriate
feedback in particular. Also a lot of progress is apparent in the
different fields in robotics with regard to learning, autonomous
behaviours, safe navigation, and manipulation. However, integrated
approaches to
1. understanding the user and her intentions,
2. transparently communicating to the user what the robot understood or
expected, and
3. designing appropriate robot behaviours based on its understanding of 
the world
are still in their infancy. These abilities have to be researched to
facilitate more effective and efficient interaction with humans using
mostly natural modalities, but also robot-specific ones, such as
visualisation techniques. Robots have to be equipped with models
enabling them to understand the users' state of mind based on multiple
modalities to an extend necessary for successful interaction. Similarly,
they have to understand and analyse their own expectations and states
and make them explicit through eligible communication channels. Thus,
topics to be covered range from recognition of verbal and non-verbal
cues from a robot's perspective that are related to the articulation of
intentions or expectations, to verbalisation and presentation techniques
that make internal processing of the robot accessible to the human
user(s). This proposed special issue aims to bundle recent advances, as
well on the understanding as also on the communication side of the
problem to mutually understand each other. It shall take a systemic
point of view, emphasising the mutual influences (e.g., a robot making
its expectation explicit will elicit an intention in the user) between
robots and users.

LIST OF TOPICS
- ways of communicating the internal state, intention, and action of a robot
- ways of communicating the robot's understanding of the interaction
- recognizing the users' expectations and intentions with a robot system
using different modalities or a combination of them
- ways of triggering and shaping user expectations with a robot by
explicit and implicit priming
- (flexible) adaptation of robot behaviour to user expectations
- verbalisation of internal robot states and processing
- verbal and non-verbal feedback
- contingent communication and mutual influences
- human-compatible perception of the world that enables the robot to
adhere to social norms
- human-compatible knowledge representations that are suitable for 
natural language communication

ON-LINE SUBMISSION
http://www.editorialmanager.com/soro/
(under 'Choose Article Type', please select: "SI: Expectations,
Intentions & Actions")

Further information about the journal
http://www.springer.com/engineering/journal/12369


GUEST EDITORS
Marc Hanheide, University of Birmingham
Manja Lohse, Bielefeld University
Hendrik Zender, German Research Center for Artificial Intelligence 
(DFKI) Saarbruecken

Best,

Manja, Hendrik, and Marc


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