[robotics-worldwide] [meetings] Final CfP - Humanoids 2014 Workshop on Policy Representation for Humanoid Robots

Ben Amor, Heni hbenamor at cc.gatech.edu
Wed Oct 22 07:47:21 PDT 2014


Final Call for Posters

*********************************************************
*                 IEEE Humanoids 2014                   *
* Workshop on Policy Representation for Humanoid Robots *
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Key Facts
=========

Humanoids 2014 Workshop, November 18, 2014
Location: Madrid, Spain

Submission Deadline: October 25, 2014 (AoE)
Notification:        October 31, 2014

URL: http://www.neil.dantam.name/2014/humanoids-policy-workshop/

Organizers
==========

Neil T. Dantam, Gerhard Neumann, Heni Ben Amor

Description
===========

Autonomous robots must handle changes in the environment,
uncertainties, and faults. They require not just predetermined plans
for a single execution path, but instead, policies describing online
response under varying conditions -- a set of execution paths. The
greater the scope of the policy, the greater the capabilities and
reliability of the robot. There are a variety of policy techniques and
system types: model-based and learned policies, continuous and
discrete state, deterministic and stochastic systems. The goal of this
workshop is to highlight recent applications of control policies for
solving complex humanoid robot tasks, as well as comparing existing
policy representations. We hope to identify policy representations
that are particularly well suited for controlling humanoid robots. We
will compare techniques for policy specification and representation,
looking for a common ground to combine assumedly disparate approaches
for autonomous capability and reliability. We strongly believe that
Humanoids 2014 is an ideal venue to shed light on recent successes and
next steps in policy representations for humanoid robots. From this
workshop, we expect participating researchers to identify and address
important challenges, techniques, and benchmarks necessary for complex
robot policy generation.

Objectives
==========

We hope to bring together outstanding researchers and graduate
students to discuss current trends, problems, and opportunities in
representing humanoid robot policies, encouraging communication and
common practices among scientists in this field. A key goal of the
workshop is to reconcile and integrate various different approaches
for policy representation. This will open new avenues to build more
comprehensive and autonomous robots. Given these insights, we want to
discuss important next steps and open problems in policy
generation. The invited speakers are renowned experts on robot
planning, control, and learning. Hence, they can contribute to a
better understanding of both the global overview of the field as well
as in-depth knowledge for their respective specialties. Researchers
will also have the opportunity to present their most recent results
and get feedback from fellow scientists and experts in the field. The
workshop is intended as an open platform for sharing and discussing
new ideas and open problems. Although robot policy representation is
the focal point of the workshop, the goal is to present this approach
in an accessible way. In this manner, we hope to familiarize members
of the audience who are new to this topic with its central concepts.

Invited Speakers
================

- Aaron Ames, Texas A&M
- Jan Peters and Guilherme Maeda, TU Darmstadt
- Marc Deisenroth, Imperial College London
- Matt Zucker, Swarthmore
- Russ Tedrake, MIT (tentative)

Topics
======

We encourage paper submissions that address the following topics:

- Present recent advances in using control policies for solving
   difficult humanoid robot control tasks.

- Compare stochastic and deterministic policies, as well as
   time-dependent vs. state-dependent policies for humanoid robots.

- Discuss how feedback, e.g., proprioceptive feedback or
   high-dimensional vision data, is integrated into policies.

- Relate different approaches for policies, such as automata, temporal
   logics, motion primitives, hybrid systems models, Markov decision
   processes, neural networks, and reward functions.

- Discuss which policy representations are best suited for robot
   learning and automatic adaptation.

- Discuss policy representation challenges specific to humanoid robots
   such as dynamic stability and many degrees of freedom.

- Discuss and compare approaches to represent and handle uncertainty
   such as Bayesian approaches, intervals, alternative events, and
   fuzzy logic.

- Compare trade-offs between explicitly modeled and implicitly learned
   policies.

- Discuss policy robustness in the presence of unmodeled conditions:
   the "unknown unknowns" problem.

- Investigate continuous versus discrete state policies for humanoid
   robots.

- Compare human-centric issues, such as ease of policy specification,
   with robot-centric issues such as computational efficiency and
   representational compactness.

- Discuss which variables should be controlled, e.g. positions,
   velocities, torques, impedance.

- Investigate the application tasks of reactive versus open loop
   controllers

Format
======

Please submit a 2-4 page paper by October 25, 2014. Submissions should
be formatted according to the conference templates and submitted via
email to policyrepresentation2014 at golems.org. Accepted posters will
be notified by October 31, 2014.

More information at
http://www.neil.dantam.name/2014/humanoids-policy-workshop/



-- 
Heni Ben Amor, Ph.D.,
Georgia Institute of Technology,
801 Atlantic Dr, Atlanta, GA 30332-0280, USA
http://henibenamor.weebly.com/


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