[robotics-worldwide] [DEADLINE Feb. 1st] CFP Autonomous Robots Journal Special Issue: Characterizing Mobile Robot Localization and Mapping

Raj Madhavan raj.madhavan at nist.gov
Tue Jan 20 10:54:51 PST 2009

[Call for Papers]
Autonomous Robots Journal Special Issue:
Characterizing Mobile Robot Localization and Mapping
Editors: Raj Madhavan, Chris Scrapper, and Alexander Kleiner

* Paper submission deadline: February 1
* Notification to authors: May 1
* Camera ready papers: August 1

Stable navigation solutions are critical for
mobile robots intended to operate in dynamic and
unstructured environments. In the context of this
special issue, stable navigation solution is
taken to mean the ability of a robotic system "to
sense and create internal representations of its
environment and estimate pose (where pose
consists of position and orientation) with
respect to a fixed coordinate frame". Such
competency, usually termed localization and
mapping, will enable mobile robots to identify
obstacles and hazards present in the environment,
and maintain an estimate of where they are and
where they have been. A myriad of approaches have
been proposed and implemented, some with greater
success than others. Since the capabilities and
limitations of these approaches vary
significantly depending on the requirements of
the end user, the operational domain, and onboard
sensor suite limitations, it is essential for
developers of robotic systems to understand the
performance characteristics of methodologies
employed to produce a stable navigation solution.

Currently, there is no way to quantitatively
measure the performance of a robot or a team of
robots against user-defined requirements.
Additionally, there exists no consensus on what
objective evaluation procedures need to be
followed to deduce the performance of various
robots operating in a variety of domains. Lack of
reproducible and repeatable test methods have
precluded researchers working towards a common
goal from exchanging and communicating results,
inter-comparing robot performance, and leveraging
previous work that could otherwise avoid
duplication and expedite technology transfer from
the "drawing board" to the field. For instance,
currently, the evaluation of robotic maps is
based on qualitative analysis (i.e. visual
inspection). This approach does not allow for
better understanding of what errors specific
systems are prone to and what systems meet the
needs. It has become common practice in the
literature to compare newly developed mapping
algorithms with former methods by presenting
images of generated maps. This procedure turns
out to be suboptimal, particularly when applied
to large-scale maps. The absence of standardized
methods for evaluating emerging robotic
technologies has caused segmentation in the
research and development communities. This lack
of cohesion hinders the attainment of robust
mobile robot navigation, in turn slowing progress
in many domains, such as manufacturing, service,
health care, and security. Providing the research
community access to standardized tools, reference
data sets, and an open-source library of
navigation solutions, researchers and consumers
of mobile robot technologies will be able to
evaluate the cost and benefits associated with various navigation solutions.

The primary focus of this special issue is to
bring together what is so far an amorphous
research community to define standardized methods
for the quantitative evaluation of robot
localization algorithms and/or robot-generated
maps. The performance characteristics of several
approaches will be documented towards developing
a stable navigation solution by detailing the
capabilities and limitations of each approach and
by the inter-comparison of experimental results,
as well as the underlying mechanisms used to
formulate these solutions. Through this effort,
we seek to start the process, which will compile
the results of these evaluations into a reference
guide that documents lessons learned and the
performance characteristics of various navigation
solutions. This will enable end users to select
the "best" possible method that meets their needs
and will also lead to the development of the
adaptive systems that are more technically
capable and at the same time are safe thus
permitting collaborative operations of man and machine.

Topics of interest include (but are not limited to):
* Characterizing navigation in complex unstructured domains &
requirements imposed by dynamic nature of operating domains
* Evaluation frameworks and adaptive approaches to developing stable
navigation solutions
* Probabilistic methodologies with particular attention to
uncertainty in assessing robot-generated maps
* Visualization tools for assessing localization and mapping
* Methods for ground truth generation from public map sources
* Multi-robot localization and mapping
* Testing in various domains of interest ranging from manufacturing
floors to urban search and rescue
* Applications with demonstrated success or lessons learnt from failures

The above topics are by no means exhaustive but
are only meant to be a representative list. We
particularly encourage submissions related to
mobile robot field deployments, challenges
encountered, and lessons learnt during such
implementations. Theoretical investigations into
assessing performance of robot localization and
mapping algorithms are also welcome. Please
contact the guest editors if you are not sure if
a particular topic fits the special issue.

See journal webiste at http://www.springer.com/10514
Manuscripts should be submitted to: http://AURO.edmgr.com
This online system offers easy and straightforward log-in and
submission procedures, and supports a wide range of submission file formats.
Raj Madhavan, Ph.D.
Intelligent Systems Division
National Institute of Standards and Technology
100 Bureau Drive, Mail Stop 8230
Gaithersburg, MD 20899-8230.

Tel: (301) 975-2865 Fax: (301) 990-9688
URL: http://aser.ornl.gov/madhavan/

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