[robotics-worldwide] [meetings] CfP IROS 15 Second Annual Workshop on Machine Learning in Planning and Control of Robot Motion

Faust, Aleksandra afaust at sandia.gov
Fri Jun 26 20:17:33 PDT 2015



CALL FOR PAPERS AND POSTER ABSTRACTS


Second Annual Machine Learning in Planning and Control of Robot Motion Workshop at

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2015

Friday, 02-Oct-2015

Hamburg, Germany

http://kormushev.com/MLPC-2015/


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IMPORTANT DATES:


Paper submission opens:             01-Jun-15

Paper submission deadline:         10-Jul-15

Notification of acceptance:           21-Aug-15

Camera-ready paper submission: 01-Sep-15

Workshop at IROS 2014:              02-Oct-15


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SUBMISSION:

Please submit a PDF document in IEEE format (page limits below) via EasyChair at

https://easychair.org/conferences/?conf=mlpc15


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ABSTRACT:

Modern robots are expected to perform complex tasks in changing environments.

Nonlinear dynamic, model uncertainty, and high-dimensional configuration

spaces make planning and executing the motions required for these tasks is

difficult. Recent success has been made through the integration of planning and

control methods with tools from machine learning.  For example, clustering,

reinforcement learning, and intelligent heuristics have adaptively solved

planning problems in complex spaces, have automatically identified appropriate

trajectories for robots with complex dynamics, and have reduced the amount of

time required for planning motions.


After the success of the First Workshop in Machine Learning in the Planning and

Control of Robot Motion at IROS 2014 in Chicago, it is the goal of this workshop

to continue to explore methods and advancements afforded by the integration of

machine learning for the planning and control of robot motion. Because these methods

are often heuristic, issues such as safety and performance are critical. Also,

learning-based questions such as problem learnability, knowledge transfer among robots,

knowledge generalization, long-term autonomy, task formulation, demonstration, role of

simulation, and methods for feature selection define problem solvability. The

objectives of this workshop are to:

- Develop a community of researchers working on machine learning methods

 in complementary fields of motion planning and controls

- Discuss current state of the art and future directions of intelligent motion

 planning and controls

- Provide for collaboration opportunities



MOTIVATION AND OBJECTIVES:

The workshop aims to spark vibrant discussion with talks from invited speakers,

presentations from authors of accepted papers, and a poster session. We are

soliciting two types of contributions:


- Papers (4-6 pages) for oral or  interactive poster presentation

- Extended abstracts (2 pages) for interactive poster presentation



LIST OF TOPICS (included, but not limited to):

- Task representation and classification

- Planning for complex and high dimensional environments

- Smart sampling techniques for motion planning

- Learning feature selection

- Methods for incorporating learning into planning

- Reinforcement learning for robotics and dynamical systems

- Transfer of learning and motion plans, knowledge and experience sharing among the agents

- Policy selection: exploration versus exploitation, methods for safe exploration

- Methods for creating motion plans that meet dynamical constraints

- Task planning and learning under uncertainty and disturbance

- Motion planning for system stability

- Adaptable heuristics for efficient motion plans

- Motion generalization - methods that learn subset of motion and produce plans with higher range of motions

- Motion planning for multi-agent systems and fleets



INTENDED AUDIENCE:

- Motion planners with interests in learning and planning for changing agents, environment, or both

- Reinforcement learning and machine learning communities that develop novel learning methods for autonomous agents

- Multi-agent researchers

- Controls community focused on controlling physical systems

- Robotics community


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CONFIRMED GUEST SPEAKERS:

- Lucian Busoniu, Technical University of Cluj-Napoca

- Danica Kragic, Royal Institute of Technology, KTH

- Jan Peters, Technischen Universität Darmstadt

- Peter Stone, University of Texas, Austin


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Please feel free to contact the workshop committee at mlpc15\AT\cs.unm.edu


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ORGANIZERS:

Aleksandra Faust, Lead Organizer, Sandia National Laboratories, afaust\AT\sandia.gov

Maria Gini, University of Minnesota, gini\AT\cs.umn.edu

Petar Kormushev, Italian Institute of Technology (IIT), petar\AT\kormushev.com

Marco Morales, Instituto Tecnologico Autonomo de Mexico, marco.morales\AT\itam.mx

Ivana Palunko, University of Dubrovnik, ivana.palunko\AT\unidu.hr

Angela P. Schoellig, University of Toronto, schoellig\AT\utias.utoronto.ca

Lydia Tapia, University of New Mexico, tapia\AT\cs.unm.edu



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