[robotics-worldwide] [meetings] CFP: Learning for Localization and Mapping Workshop at IROS 2017 - Extended Deadline

Igor Gilitschenski igilitschenski at ethz.ch
Tue Aug 1 04:56:40 PDT 2017

Call for Papers

Learning for Localization and Mapping Workshop at IROS 2017

Vancouver, B.C., Canada, September 28, 2017

Website: https://urldefense.proofpoint.com/v2/url?u=https-3A__sites.google.com_site_learningforslam_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=UIIqaNTggdM6iogsB3veCj-7lz5Hidy_whkMKHAbf0M&s=ni3S3uUur-qx1Zydr1vRV34TDBZkBz9qTFX6AeOUYUg&e= 

===== OVERVIEW =====

The goal of this workshop is to present and discuss developments in
learning-based approaches for localization and mapping systems. We aim
at bridging the gap between robotics and machine learning research by
bringing together researchers from both fields. This workshop focuses on
developing a clear vision for future directions of research of
learning-based mapping techniques and novel machine learning algorithms
that promise to further bolster localization and mapping systems.

We invite you to submit a papers abstract on any potential topic within
the scope of the workshop. The abstracts can be submitted in IROS format
(4-6 pages, references will go on an extra page). Accepted papers will
be presented in a poster session. The pdf of the posters alongside with
the abstracts will be published on the workshop website.


The topics of interest involve but are not limited to:

* Improving distinctiveness of place representations for place
  recognition and loop closure.

* Learning-based approaches for map maintenance and map compression.

* Selecting useful landmarks for map creation.

* Multi-modal landmark descriptors and matching between different
  sensor types.

* Representation of objects as landmarks in SLAM.

* Deployment of learning-based approaches on resource constrained
  robotic platforms.

* Uncertainty quantification for deep learning and its applicability in
  a Bayesian fusion setting.

* Success stories and lessons learned (including negative results).


We are proud to have a group of famous invited speakers presenting at
our workshop involving

Wolfram Burgard, University of Freiburg

Jana Kosecka, George Mason University

Stefan Leutenegger, Imperial College London

Marc Pollefeys, Microsoft

Fabio Ramos, University of Sydney

Bernhard Zeisl, Google

===== ORGANIZERS =====

Cesar Cadena, ETH Zurich

Igor Gilitschenski, ETH Zurich

John Leonard, MIT

Sudeep Pillai, MIT

Fabio Ramos, University of Sydney

Niko Suenderhauf, QUT

===== DATES =====

Submission of Paper Drafts (extended): August, 11th
New Notification of Acceptance Date: August, 18th
New Submission of Final Version Deadline: September, 1st
Date of Workshop: September, 28th

===== CONTACT =====

The organization committee can be reached at
learningforslam at googlegroups.com
Dr.-Ing. Igor Gilitschenski
ETH Zürich
Autonomous Systems Lab
LEE J317
Leonhardstrasse 21
8092 Zürich

Phone: +41 44 63 29 787
igilitschenski at ethz.ch

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