[robotics-worldwide] Call for Posters - ICRA 2013 Workshop on "Novel Methods for Learning and Optimization of Control Policies and Trajectories for Robotics" - Second Call

Gerhard Neumann geri at robot-learning.de
Sun Mar 3 06:01:03 PST 2013


CALL FOR POSTERS - SECOND CALL


ICRA 2013 WORKSHOP ON "NOVEL METHODS FOR LEARNING AND OPTIMIZATION OF 
CONTROL
POLICIES AND TRAJECTORIES FOR ROBOTICS""

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QUICK FACTS
Organizers:	Katja Mombaur, Gerhard Neumann, Martin Felis, Jan Peters
Conference:	ICRA 2013
Location:	Karlsruhe, Germany
Workshop Date and Time:	Friday, May 10, 2013, 9:00 - 18:30
Website:	http://www.robot-learning.de/Research/ICRA2013
Poster Submission Deadline: March 15, 2013
Poster Acceptance Notification: March 20, 2013
Submission Form: 1 page extended abstract

ABSTRACT
The current challenges defined for robots require them to automatically 
generate and control a wide range of motions in order to be more 
flexible and adaptive in uncertain and changing environments. However, 
anthropomorphic robots with many degrees of freedom are complex 
dynamical systems. The generation and control of motions for such 
systems are very demanding tasks. Cost functions appear to be the most 
succinct way of describing desired behavior without over- specification 
and appear to underlie human movement generation in pointing/reaching 
movement as well as locomotion. Common cost functions in robotics 
include goal achievement, minimization of energy consumption, 
minimization of time, etc. A myriad of approaches have been suggested to 
obtain control policies and trajectories that are optimal with respect 
to such cost function. However, to date, it remains an open question 
what is the best algorithm for designing or learning optimal control 
policies and trajectories in robotics would work. The goal ofthis 
workshop is to gather researchers working in robot learning with 
researchers working in optimal control, in order to give an overview of 
thestate of the art and to discuss how both fields could learn from each 
other and potentially join forces to work on improved motion generation 
andcontrol methods for the robotics community. Some of the core topics are:
- State of the art methods in model-based optimal control and model 
predictive control for robotics as well as inverse optimal control
- State of the art methods in robot learning, model learning, imitation 
learning, reinforcement learning, inverse reinforcement learning, etc .
- Shared open questions in both reinforcement learning and optimal 
control approaches
- How could methods from optimal control and machine learning be combined?


FORMAT
The workshop will consist of presentations, posters, and panel 
discussions. Topics to be addressed include, but are not limited to:

- How far can optimal control approaches based on analytical models come?
- When using learned models, will the optimization biases be increased 
orreduced?
- Can a mix of analytical and learned models help?
- Can a full Bayesian treatment of model errors ensure high performance 
in general?
- What are the advantages and disadvantages of model-free and 
model-basedapproaches?
- How does real-time optimization / model predictive control relate to 
learning?
- Is it easier to optimize a trajectory or a control policy?
- Which can be represented with fewer parameters?
- Is it easier to optimize a trajectory/control policy directly in 
parameter space or to first obtain a value function for subsequent 
backwards steps?
- Is less data needed for learning a model (to be used in optimal 
control, or model-based reinforcement learning) or for directly learning 
an optimal control policy from data?
- What applications in robotics are better suited for model-based, 
model-learning and model-free approaches?

All of these questions are of crucial importance for furthering the 
state-of-the-art both in optimal control and in robot reinforcement 
learning. The goal of this workshop is to gather researchers working in 
robot learning with researchers working in optimal control, in order to 
give an overview of the state of the art and to discuss how both fields 
could learn from each other and potentially join forces to work on 
improved motion generation and control methods for the robotics community.


IMPORTANT DATES
March 15 - Deadline of submission for Posters
March 20th - Notification of Poster Acceptance


SUBMISSIONS
Extended abstracts (1 pages) will be reviewed by the program committee 
members on the basis of relevance, significance, and clarity. Accepted 
contributions will be presented as posters but particularly exciting 
work maybe considered for talks. Submissions should be formatted 
according to the conference templates and submitted via email 
toneumann at ias.tu-darmstadt.de.

ORGANIZERS
Katja Mombaur, Universitaet Heidelberg
Gerhard Neumann, Technische Universitaet Darmstadt
Martin Felis, Universitaet Heidelberg
Jan Peters, Technische Universitaet Darmstadt and Max Planck Institute 
for Intelligent Systems

LOCATION AND MORE INFORMATION
The most up-to-date information about the workshop can be found on the 
ICRA 2013 webpage.




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