[robotics-worldwide] Call for Posters - ICRA 2013 Workshop on "Novel Methods for Learning and Optimization of Control Policies and Trajectories for Robotics" - Second Call
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
POLICIES AND TRAJECTORIES FOR ROBOTICS""
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
Poster Submission Deadline: March 15, 2013
Poster Acceptance Notification: March 20, 2013
Submission Form: 1 page extended 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
- How could methods from optimal control and machine learning be combined?
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
- Can a mix of analytical and learned models help?
- Can a full Bayesian treatment of model errors ensure high performance
- What are the advantages and disadvantages of model-free and
- How does real-time optimization / model predictive control relate to
- 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
- 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.
March 15 - Deadline of submission for Posters
March 20th - Notification of Poster Acceptance
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.
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.
More information about the robotics-worldwide