[robotics-worldwide] [meetings] Call for Participation IROS 14 Workshop on Machine Learning in Planning and Control of Robot Motion

Aleksandra Faust afaust at cs.unm.edu
Mon Sep 8 23:11:44 PDT 2014


Please join us for:
Machine Learning in Planning and Control of Robot Motion Workshop at 
IROS 2014 in Chicago, IL.

Location: Salon 3
Time: 8:30 - 5:00, Sunday, September 14, 2014

Program now available at: 
https://www.cs.unm.edu/amprg/mlpc14Workshop/schedule.html
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Please feel free to contact the workshop committee at 
mlpc2014\AT\easychair.org
Website: http://www.cs.unm.edu/amprg/mlpc14Workshop

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INVITED SPEAKERS:
Pieter Abbeel, University of California Berkeley
Jan Peters, Technische Universitaet Darmstadt
Manuela Veloso, Carnegie Mellon University
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ABSTRACT:
Modern robots are expected to perform complex, unsafe, or difficult 
tasks. Planning and executing the motions required for these tasks is 
difficult due to factors such as high-dimensional configuration spaces 
and changing environmental conditions. Moreover, uncertainty in robot 
dynamics and environment makes it impossible to know ahead of time how 
to operate best. Recent success has been made through the integration of 
planning methods with tools from Machine Learning (ML). For example, 
clustering, reinforcement learning, and intelligent heuristics have 
adaptively solved planning problems in complex planning spaces, 
automatically identified appropriate trajectories for robots with 
complex dynamics, and reduced the amount of time required for planning 
motions.

It is the goal of this workshop to explore methods and advancements 
afforded by the integration of ML for the planning and execution 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. We will address these issues while discussing current and 
future directions for intelligent planning and execution of motions for 
robotics systems.

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.

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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ORGANIZERS:
Maria Gini, University of Minnesota, gini\AT\cs.umn.edu
Marco Morales, Instituto Tecnologico Autonomo de Mexico, 
marco.morales\AT\itam.mx
Angela P. Schoellig, University of Toronto, schoellig\AT\utias.utoronto.ca
Lydia Tapia, University of New Mexico, tapia\AT\cs.unm.edu
Aleksandra Faust - Student Organizer, University of New Mexico, 
afaust\AT\cs.unm.edu
Farbod Farshidian - Student Organizer, ETH Zurich, 
farshidian\AT\mavt.ethz.ch








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