[robotics-worldwide] [meetings] 2nd CFP: ICRA 2018 Workshop on Cognitive Robotics and AI

David Rajaratnam David.Rajaratnam at unsw.edu.au
Mon Apr 2 03:31:32 PDT 2018


            New Horizons in Cognitive Robotics and AI:
      Exploiting Recent Advances for Predictive Control and
             Prospective Interaction between Agents

                            Friday 25 May, 2018
                            Brisbane, Australia
                          (An ICRA 2018 workshop)

             URL: https://urldefense.proofpoint.com/v2/url?u=http-3A__btcc.nagoya.riken.jp_icraworkshop2018_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=g4tZUs2wqMop-uDZa2f5q5dUocGhJFnTzs2vSiwkaCo&s=X-dIvA1LKQE_lYHgUlz1AKTIqEiXQqExjhZ1VuVCbEo&e=


Submission deadline (extended): April 18th, 2018
Notification of acceptance (extended): April 24th, 2018


Advances in artificial intelligence (AI) have resulted in a wide range of
commercial and industrial applications. Coupled with developments in
sensing technologies, AI has also seen important applications to robotics;
especially in areas such as robot vision, mapping and localization.

Despite these advances, the impact of AI to the area of robot behavior and
control has been more modest. While AI based languages and tools for
high-level robot control have been developed, nevertheless there is still
considerable effort required to understand how to robustly embed these
high-level control paradigms within low-level robot controllers and

Robots are generally controlled with feedback control loops. Feedback
control loops respond to environmental changes in real-time, coping with
the uncertainty of the environment through controller robustness. One of
the important characteristic of a strong coupling of AI and robot control
is to control robot behaviors with predictions of future events beyond
simple real-time responses to environmental changes.

In this multi-disciplinary workshop, we will discuss the problem of
integrating high-level and low-level robot control. This workshop
represents a collaboration between the AI-based cognitive robotics
community (CogRob) and members of the IEEE Technical Committee on Cognitive
Robotics (CoRo).


This workshop aims to bring together researchers from a wide range of
disciplines with an interest in robot behavior and control. The workshop is
concerned with foundational research questions within cognitive robotics,
as well as robotic system design and robotic applications that utilize AI


We invite submissions of short research papers from all researchers and
practitioners interested in AI and robotics, and their integration.

Topics of interests include (but are not limited to) cognitive robotics,
adaptive robotics, robot control, knowledge representation and reasoning,
reasoning and robot planning under uncertainty, diagnostic reasoning,
machine learning, symbol grounding, cognitive science, cognitive vision,
perception, motion planning, human-robot interaction, and AI for robotics.

We especially welcome discussions and demonstrations of robotic
applications and implemented robotic systems that utilize AI methods.


Potential participants are invited to submit an extended abstract (i.e., a
position paper describing specific questions and issues that the
participants feel should be addressed; a demo paper describing a
demonstration of a robotic application, system or tool; a technical
communication aimed at describing recent developments, and new projects
that are not ready for publication as regular papers).

All papers will be presented at a poster session during the workshop.


Submissions are accepted in PDF format only
Submission format:
- Extended abstract of up to 1 page.
- Author names and authors affiriations should be included.
- Papers must be submitted by the due date at the following EasyChair
  submission site:



The workshop contributions will be available electronically.


Shingo Shimoda, RIKEN Brain Science Institute, Japan

David Rajaratnam, University of New South Wales, Australia

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