[robocup-athome] [meetings] IROS 2017 Workshop: Semantic Policy and Action Representations for Autonomous Robots (SPAR)

Karinne Ramirez Amaro karinne.ramirez at tum.de
Tue Jun 6 20:16:38 UTC 2017

****2nd Workshop on Semantic Policy and Action Representations for 
Autonomous Robots (SPAR)***
----Call for Posters and Demonstrations---

We are calling for contributions to our IROS 2017 workshop. We would 
like to invite the attendees of this workshop to submit an extended 
abstract explaining their current work or developed systems in the areas 
of reasoning, perception, control, planning, and learning applied to 
robotic systems.

This workshop is intended for roboticists interested in improving the 
reliability and autonomy of robots. We hope to bring together 
outstanding researchers and graduate students to discuss current trends, 
problems, and opportunities in semantic action (policy) representations, 
encouraging communication and common practices such as sharing datasets 
among scientists in this field.

*** Important Dates ***:
Paper submission deadline: 25th July 2017
Notification of acceptance: 15th August 2017
Camera ready submission: 1st September 2017
Workshop day: 24th September 2017

*** Call for contributions ***
We encourage 1-2 pages extended abstract of relevant work that has been 
previously published, or is to be presented at the main conference. The 
accepted abstracts will be posted on the workshop website in a compiled 
yearbook and will not appear in the official IEEE proceedings. 
Furthermore, we particularly call for live demonstrations to be 
presented on the workshop day. We encourage researchers as well as 
companies (both hardware and software companies) to contribute to the 
workshop. The reviewing is single blind and will be carried out by the 
workshop chairs.

Please submit your abstract to the workshop official email address 
<spar.workshop at gmail.com> before July 25, 2017.

The accepted demonstrations can show their systems and its benefits to a 
broader audience. The accepted papers will have the opportunity to 
present their work/ideas in a poster session. Two selective submissions 
will give a 15 min talk at the workshop. Please indicate in your email 
if you want to present as a poster, oral, and/or live demonstration.

Furthermore, a selective number of papers from the poster sessions will 
be invited to submit their novel work to the Special Issue we are 
proposing in the journal “Robotics and Autonomous Systems”. This special 
issue will cover the main topics of interest of this workshop.

***Workshop URL***
Contact email:  spar.workshop at gmail.com

*** Workshop objectives ***

The aim of this one-day workshop is two-fold. First, we intend to 
highlight to the robotics community the recent developments in semantic 
reasoning representations and semantic policy generation from low level 
(sensory signal) to high level (planning and execution). More 
importantly, we want to reconcile and integrate various bottom-up and 
top-down approaches for semantic action perception and executions in 
different domains. Second, we are aiming to compare various 
state-of-the-art approaches for generic action and reasoning 
representations in both computer vision and robotic communities, looking 
for a common ground to combine assumedly different approaches for 
autonomous capability and reliability. For this, we would like to 
propose and define different data sets that could be potentially used as 
benchmarks to compare the presented methods. We would like to take 
advantage of the recent efforts that some laboratories took by making 
their testing data sets publicly available. In addition, we would like 
to encourage this best practice to the participants of this workshop.

This workshop will present the main benefits of this new emerging type 
of methods such as allowing robots to learn generalized semantic models 
for different domains. We will also like to discuss the next 
breakthrough topics in this area, e.g. the scalability of the learned 
models that can adapt to new scenarios/domains in a way that the robot 
can transfer all the acquired knowledge and experience from existing 
data to new domains with very little human intervention.

Topics of interest include, but are not limited to:
  *AI-Based Methods
     --Learning and adaptive systems & Probability and statistical methods
     --Action grammars/libraries  & Spatiotemporal event encoding
     --Machine learning techniques for semantic representations
  *Reasoning Methods in Robotics and Automation
    --Signal to symbol transition (Symbol grounding) & Different levels 
of abstraction
    --Semantics of manipulation actions & Semantic policy representation
    --Context modeling methods
  *Human Behavior Recognition
    --Learning from demonstration & Object-action relations
    --Bottom-up and top-down perception
  *Task, Geometric, and Dynamic Level Plans and Policies
    --PDDL high-level planning & Task and motion planning methods
  *Human-Robot interaction
    --Prediction of human intentions & Linking linguistic and visual data

*** Invited Speakers *** (in alphabetical order, all confirmed)

1) Yiannis Aloimonos University of Maryland, USA
2) Tamim Asfour Karlsruhe Institute of Technology, Germany
3) Heni Ben Amor Arizona State University, USA
4) Gordon Cheng Technische Universität München, Germany
5) Gregory D. Hager, Johns Hopkins University, USA
6) Tetsunari Inamura, National Institute of Informatics, Japan
7) Lydia E. Kavraki, Rice University, USA
8) Manuela M. Veloso, Carnegie Mellon University, USA

*** Organizers ***

Karinne Ramirez-Amaro, Technical University of Munich, 
Yezhou Yang, Arizona State University, USA, 
Neil T. Dantam, Rice University, http://www.neil.dantam.name
Eren Erdal Aksoy, Karlsruhe Institute of Technology, 
Gordon Cheng, Technical University of Munich, 

Dr.-Ing. Karinne Ramirez Amaro
Institute for Cognitive Systems
Technische Universitaet Muenchen

Address: Karlstr. 45, 2.OG. 80333 Munich, Germany
Room: 2008
Web page: http://web.ics.ei.tum.de/~karinne/Ramirez/index.html
email: karinne.ramirez at tum.de
Telephone: +49-89-289-26791

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