[robotics-worldwide] [meetings] Call for Contributions: RSS 2014 Workshop on Autonomous Control, Adaptation, and Learning for Underwater Vehicles

M. Ani Hsieh mhsieh1 at drexel.edu
Tue Apr 22 09:17:01 PDT 2014

Apologies for multiple postings.


We solicit 2-page extended abstracts to be included in the

RSS 2014 Workshop on
Autonomous Control, Adaptation, and Learning for Underwater Vehicles
1-Day Workshop, July 12, 2014
Berkeley, CA

as a poster presentation and short spotlight talk.

Web Address:



Extended Abstract Submission: May 9, 2014
Extended Abstract Notification: May 16, 2014
Workshop Date: July 12, 2014



RSS 2-column format, max. 2 pages, please use the template available at:


Extended abstracts should be submitted via email to Ryan Smith (rnsmith
_at_ fortlewis _dot_ edu) with the phrase "RSS 2014 ACALUV Workshop" in the
subject line.

Accepted contributions will be given a poster presentation (plus spotlight
talk) at the workshop.



There has been a steady increase in the deployment of autonomous underwater
and surface vehicles (AUVs and ASVs) for applications such as hazardous
waste mitigation, inspection and intervention for marine structures,
environmental monitoring, and tracking of various biological, chemical, and
physical processes. These emerging applications require solving unique
challenges that arise when working in the underwater environment. The lack
of reliable wireless communications between robots and a base station or
with other robots makes remote control difficult, underwater vehicle
dynamics are tightly coupled with the environmental dynamics making
controls hard, and well-understood perception technologies do not always
apply to the underwater environment. These challenges, in addition to our
limited understanding of the complexities of the fluidic environment, make
closed-loop control, online learning, and adaptive decision making
difficult at best.

The purpose of this workshop is to bring together experts in the highly
interdisciplinary field of autonomous underwater robotics to bridge the gap
between (1) modeling and prediction for closed-loop control and (2) online
learning and adaptation in highly dynamic and uncertain environments.
Specifically we would like to highlight new work that lies at the
intersection of robotics, control theory, artificial intelligence, machine
learning, ocean science, and transport theory that addresses issues in
modeling and prediction of the underwater environment. The techniques
developed in this workshop will lead to improvements in control, learning,
and adaptation for underwater systems that are paramount to effectively
carrying out missions and achieving persistent autonomy in these

We solicit 2-page extended abstracts to be included in the workshop as a
poster presentation and short spotlight talk. Papers spanning one or more
of the following topic areas are particularly encouraged:

   - Motion Planning and Control
   - Environmentally Constrained Path Planning
   - Single and Multi-Agent Control
   - Modeling and Prediction of Dynamic and Uncertain Environments
   - Online Learning
   - Distributed Control
   - Coordination of Heterogeneous Systems
   - Applications in Field Robotics
   - Cloud Robotics
   - Novel Testbeds, Actuators and Sensors



Christopher Clark, Harvey Mudd College, Confirmed
Geoff Hollinger, Oregon State University, Confirmed
Franz Hover, MIT, Confirmed
M. Ani Hsieh, Drexel University, Confirmed
Ryan Smith, Fort Lewis College, Confirmed
Pierre Lermusiaux, MIT, Confirmed
Fumin Zhang, GA Tech, Confirmed
Ryan Eustice, University of Michigan, Confirmed
David P. Williams, NATO CMRE, Confirmed
Doug Horner, Naval Postgraduate School, Confirmed
Noel DuToit, Naval Postgraduate School, Confirmed



S.K. Gupta, NSF, Confirmed
Signe Redfield, Naval Research Labs, Confirmed
Jason Stack, ONR, Confirmed but Tentative
Marc Steinberg, ONR, Confirmed but Tentative



Geoff Hollinger, Oregon State University
Franz Hover, MIT
M. Ani Hsieh, Drexel University
Ryan N. Smith, Fort Lewis College

For questions, please contact Ryan Smith (rnsmith _at_ fortlewis _dot_

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