[robotics-worldwide] [meetings] Final CFP: ICRA 2018 Workshop on Machine Learning in Planning and Control of Robot Motion

Lewis Chiang lewis.prometheus at gmail.com
Mon Mar 12 09:02:02 PDT 2018

*Apologies for cross postings*

Third Machine Learning in Planning and Control of Robot Motion Workshop at
ICRA 2018May 21, 2018 -- Brisbane, Australia
Website: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.cs.unm.edu_amprg_Workshops_MLPC18_&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=7RqoilrlNoxo3nMammC1Zxj9Qeq2VgMNkibKTe2WmCQ&s=DV_un3_F-BUKQEVru1eyWLQSip9mXpyIgdAbplS1Z-I&e=
Submission deadline: March 21, 2018
Contact: mlpc18 at googlegroups.com


The workshop aims to spark vibrant discussion with talks from invited
speakers, presentations from authors of accepted papers, and a poster
session. Because machine learning 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.

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


Topics of interest

Topics include, but are 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
- 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


Submission details

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

More information about the workshop is available at:

The Call for Papers is available at:


Important dates

Submission deadline: March 21, 2018
Acceptance notification: April 23, 2018
Camera-ready deadline: May 15, 2018
Workshop: May 21, 2018



- Aleksandra Faust, Google Brain, USA
- Tsz-Chiu Au, Ulsan National Institute of Science and Technology, South
- James Davidson, Google Brain, USA
- Hanna Kurniawati, University of Queensland, Australia
- Lydia Tapia, University of New Mexico, USA
- Hao-Tien Lewis Chiang, University of New Mexico, USA

0 New

Hao-Tien (Lewis) Chiang

PhD student, Department of Computer Science
University of New Mexico
Email: lewispro at unm.edu, Url: https://urldefense.proofpoint.com/v2/url?u=https-3A__www.cs.unm.edu_amprg&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=7RqoilrlNoxo3nMammC1Zxj9Qeq2VgMNkibKTe2WmCQ&s=6-Udbqs0K9zKQvkgUoAhOnE-VxrGJ6efI1r4GgyoQ2U&e=

More information about the robotics-worldwide mailing list