[robotics-worldwide] [journals] CfP: Autonomous Robots SI - Towards Long-Term Autonomy in Marine Robotics

Francesco Maurelli f.maurelli at ieee.org
Fri Oct 3 12:25:55 PDT 2014


FOLLOWING MANY REQUESTS, NEW DEADLINE: 8th December 2014

SPRINGER AUTONOMOUS ROBOTS
Special Issue Call for Papers
Towards Long-Term Autonomy in Marine Robotics

website: http://osl.eps.hw.ac.uk/article.php?articleID=19

pdf: 
http://osl.eps.hw.ac.uk/files/uploads/AURO%20CFP%20-%20Marine%20Robotics.pdf

Guest Editors:
Marc Carreras, University of Girona, Spain
David Lane, Heriot-Watt University, United Kingdom
Francesco Maurelli, Heriot-Watt University, United Kingdom
Kanna Rajan, MBARI, United States

In recent years, persistent autonomous operations have become a key area 
of interest for marine robotics researchers. As hardware costs have 
plummeted, sensors measuring various oceanographic properties have 
proliferated and the use of robotic platforms within the ocean science 
community has increased, the need for increased autonomy to perform 
tasks over large spatial and temporal durations. The challenge in doing 
so, is particularly severe in the context of the marine environment 
however, and especially for robotic assets to be observable and 
communicable over space and time. Over and beyond making time-series 
measurements marine robots have demonstrated their capability to respond 
to episodic events, perform targeted sample collection, track dynamic 
phenomenon in rough coastal environments and make quasi-synoptic 
observations in the meso-scale.
However, there continue to be significant challenges to marine robotic 
operations. While commercial deep-water oilfield inspection with 
autonomous vehicles is now a commercial reality, fielded robots continue 
to rely heavily on accurate a priori models of the subsea assets and 
expose limited capabilities for autonomous decision making.
Most autonomous vehicles in the marine environment are limited to 
preplanned missions, or to limited forms of autonomy involving script 
switching and re-parametrisation in response to pre-programmed events. 
Realizing the persistent autonomy that users in the ocean increasingly 
demand is involving a greater capability in understanding sensed events 
to detect failure and error, and more capable task planning approaches 
that can adapt behaviour and control in novel ways.

Topics of interest include, but are not limited to:
- Autonomous long-term navigation, localization and SLAM
- Automated dynamic re-planning, planning under uncertainty
- Semantic-based world modelling, probabilistic approaches in ontologies
- Architectures for long-term autonomy
- Robust learning techniques
- Probabilistic graphical models
- Bio-inspired and bio-mimetic approaches
- Multi-vehicle cooperation potentially in multiple domains (air, 
surface, underwater)

In this special issue of Autonomous Robots journal, we invite:
- Research papers to report innovative work in the field (up to 20 pages)
- Applied research case-studies to analyse industrial needs, current 
states and needs for current and future operations (up to 20 pages)
Systems which exhibit these novel techniques should either be used on 
real-world marine robots, field experiments or demonstrations or authors 
should clearly demonstrate how they would transition such systems to the 
real world.

Manuscripts must be submitted to: http://AURO.edmgr.com. Choose 
“Long-term autonomy in Marine Robotics” as the article type.

For more information, please contact the guest editors at: 
auro-marine at googlegroups.com


-- 
Francesco Maurelli
Ocean Systems Laboratory
Heriot-Watt University
f.maurelli at ieee.org


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