[robotics-worldwide] [journals] CFP: Special Issue on Simultaneous Location and Mapping (SLAM) Focused on Mobile Robotics - an open access journal publishes its 7th volume by MDPI

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[robotics-worldwide] [journals] CFP: Special Issue on Simultaneous Location and Mapping (SLAM) Focused on Mobile Robotics - an open access journal publishes its 7th volume by MDPI

Ms. Elsie Zhao / MDPI
Dear Colleagues,

I am pleased to introduce this Special Issue on “Simultaneous Location
and Mapping (SLAM) Focused on Mobile Robotics”. This Special Issue is of
fundamental importance in the current robotics area for at least three
main reasons. First of all, environment mapping is paramount for the
Perception Action (PA) loop in many robotics applications and Augmented
Reality (AR) human–robot–environment interaction. In the last few years,
new and emerging technologies have enabled the acquisition of
high-quality and robust maps in several scenarios with low effort in
terms of both budget and coding. Last, but not least, new algorithms
have shown that the drift problem can be drastically reduced using new,
non-recursive, approaches or cooperative methods. As a consequence, we
face a great opportunity to spread robotics applications to several new
fields where, due to technology limitations or budget restrictions,
robotics have not yet been properly exploited.

The Perception–Action loop is basic in control and robotics applications
where the variable to control, or the object to reach and
manipulate/pick, must, first of all, be sensed, i.e., perceived. For
modern and ever-more complex robotics and artificial intelligence-based
mobile robotics applications, context awareness is fundamental along
with the possibility of locating an agent within a current and updated
map. When the man is one of the agents within the loop, thanks to
Augmented Reality technologies, the map of landmarks and/or the 3D
reconstruction of the environment, together with ego-location, are able
to enable high fidelity and fully-immersive augmented human perception

Emerging technologies embed several sources of information, such as
traditional cameras, stereo, 3D time-of-flight cameras, gyroscopes, and
magnetometers with processing capabilities. A real-time algorithm
running onboard a proper DPU, GPU or neural network is able to then fuse
that information in order to provide a map and location inside a
currently updated map. Examples comprise Microsoft HoloLens, Intel
RealSense, and other solutions that are able to recover an ambient map
after just a quick tour inside it.

Furthermore, the algorithms serving as the basis of SLAM were, for many
years, based on recursive Kalman-like filtering that, unfortunately, was
not able to solve the drift problem. Mobile robotics are, in fact, prone
to drift because mobile robots are non-holonomous systems. One current
solution exploits graph theory to simultaneously take into consideration
the signal correlation among all the robot routes. Other solutions make
use of several agents equipped with different acquisition systems in a
collaborative approach.

The objective of this Special Issue is, therefore, to promote a deeper
understanding of major conceptual and technical challenges, and to
facilitate the spread of recent breakthroughs in SLAM for mobile
robotics. This Special Issue, by achieving this objective, is expected
to spread the state-of-the-art to new frontiers of robotics applications.

Topics of interest include (but are not limited to):

     New algorithms for SLAM (G-SLAM, multivehicle/cooperative SLAM, etc.)
     Sensing technologies for SLAM
     Map and location output metrological calibration
     Development of new applications enabled by emerging technologies
(Microsoft HoloLens, Intel RealSense, etc.)
     Augmented Reality to exploit SLAM applications for vehicle safety in
path planning and control

Assoc. Prof. Mariolino De Cecco
Dr. Alberto Fornaser
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering
and logging in to this website. Once you are registered, click here to
go to the submission form. Manuscripts can be submitted until the
deadline. All papers will be peer-reviewed. Accepted papers will be
published continuously in the journal (as soon as accepted) and will be
listed together on the special issue website. Research articles, review
articles as well as short communications are invited. For planned
papers, a title and short abstract (about 100 words) can be sent to the
Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be
under consideration for publication elsewhere (except conference
proceedings papers). All manuscripts are thoroughly refereed through a
single-blind peer-review process. A guide for authors and other relevant
information for submission of manuscripts is available on the
Instructions for Authors page. Robotics is an international
peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a
manuscript. The Article Processing Charge (APC) for publication in this
open access journal is 350 CHF (Swiss Francs). Submitted papers should
be well formatted and use good English. Authors may use MDPI's English
editing service prior to publication or during author revisions.


Simultaneous Location And Mapping
Map building for Augmented Reality
Mobile Robotics

Robotics (ISSN 2218-6581; https://urldefense.proofpoint.com/v2/url?u=http-3A__www.mdpi.com_journal_robotics&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=dR0wk-T4xRgLwCwrOCIWfVckGiL1LsDje2lXjKmUkc8&s=u0t50fRYiwUBBWoIRomYE7EXMy866wnOIvcx5wsDv0U&e=) is a
journal published by MDPI AG, Basel, Switzerland. Robotics maintains
rigorous peer-review and a rapid publication process. All articles are
published with a CC BY 4.0 license. For more information on the CC BY
license, please see: https://urldefense.proofpoint.com/v2/url?u=http-3A__creativecommons.org&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=dR0wk-T4xRgLwCwrOCIWfVckGiL1LsDje2lXjKmUkc8&s=XOeVTFsbZ67OnlT7sS3fI-Of3kOJu7mGXN2M03YNSfE&e=

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