[Call for Papers] Autonomous Robots Journal Special Issue: Characterizing Mobile Robot Localization and Mapping

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

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.

IMPORTANT DATES
* Paper submission deadline: February 1, 2009
* Notification to authors: May 1, 2009
* Camera ready papers: August 1, 2009

SUBMISSION INFORMATION
See journal webiste at http://www.springer.com/10514
Manuscripts should be submitted to: http://AURO.edmgr.com
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