Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Positioning and Localization in Mobile Robots and Intelligent Transportation Systems
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Positioning and Localization in Mobile Robots and Intelligent Transportation Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (25 February 2022) | Viewed by 3219

Special Issue Editors

Dr. Jonay Toledo

E-Mail Website
Guest Editor
Computer Science Department, University of La Laguna, 38200 San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
Interests: mobile robotics; sensor fusion; embedded robotics; intelligent vehicles
Prof. Dr. Leopoldo Acosta

E-Mail Website
Guest Editor
Computer Science Department, University of La Laguna, 38200 San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
Interests: automatic control; robotics; intelligent vehicles

Special Issue Information

Dear Colleagues,

The key to the success of a mobile robot or an intelligent transportation system its correct localization in the environment as the first step, and all the decision making during navigation and planning stacks are based on navigation. Any error in the localization system can lead to complete system failure, or to the stack being in a nonrecoverable situation. Localization is also used in automatic mapping, aerial image reconstruction, and many other projects.

Every project is different, with a specific design in terms of the structure, locomotion system, available sensors, or the environment where it moves, so the localization system must be specifically adapted and is highly dependent on the application. In some cases, standard techniques are not useful due to the characteristics of the prototype.

This Special Issue is centered on all the topics related with automatic localization both outdoor and indoors, including localization sensors, sensor fusion, localization algorithms, new sensor techniques, and all aspects related to localization in any system.

Dr. Jonay Toledo
Prof. Dr. Leopoldo Acosta
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 submissions that pass pre-check are 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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.

Keywords

  • localization
  • mobile robot
  • sensor fusion
  • Kalman filter
  • particle filter
  • localization filter
  • range sensor
  • local positioning system
  • global positioning system
  • vision-based localization
  • odometry
  • underwater localization
  • statistical localization
  • aerial localization
  • inertial localization
  • WiFi localization
  • WiFi positioning system
  • radio frequency-based indoor localization
  • ultrasonic localization
  • laser localization

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

23 pages, 8283 KiB  
Article
Nonuniform Dual-Rate Extended Kalman-Filter-Based Sensor Fusion for Path-Following Control of a Holonomic Mobile Robot with Four Mecanum Wheels
by Ricardo Pizá, Rafael Carbonell, Vicente Casanova, Ángel Cuenca and Julián J. Salt Llobregat
Appl. Sci. 2022, 12(7), 3560; https://doi.org/10.3390/app12073560 - 31 Mar 2022
Cited by 10 | Viewed by 2680
Abstract
This paper presents an extended Kalman-filter-based sensor fusion approach, which enables path-following control of a holonomic mobile robot with four mecanum wheels. Output measurements of the mobile platform may be sensed at different rates: odometry and orientation data can be obtained at a [...] Read more.
This paper presents an extended Kalman-filter-based sensor fusion approach, which enables path-following control of a holonomic mobile robot with four mecanum wheels. Output measurements of the mobile platform may be sensed at different rates: odometry and orientation data can be obtained at a fast rate, whereas position information may be generated at a slower rate. In addition, as a consequence of possible sensor failures or the use of lossy wireless sensor networks, the presence of the measurements may be nonuniform. These issues may degrade the path-following control performance. The consideration of a nonuniform dual-rate extended Kalman filter (NUDREKF) enables us to estimate fast-rate robot states from nonuniform, slow-rate measurements. Providing these estimations to the motion controller, a fast-rate control signal can be generated, reaching a satisfactory path-following behavior. The proposed NUDREKF is stated to represent any possible sampling pattern by means of a diagonal matrix, which is updated at a fast rate from the current, existing measurements. This fact results in a flexible formulation and a straightforward algorithmic implementation. A modified Pure Pursuit path-tracking algorithm is used, where the reference linear velocity is decomposed into Cartesian components, which are parameterized by a variable gain that depends on the distance to the target point. The proposed solution was evaluated using a realistic simulation model, developed with Simscape Multibody (Matlab/Simulink), of the four-mecanum-wheeled mobile platform. This model includes some of the nonlinearities present in a real vehicle, such as dead-zone, saturation, encoder resolution, and wheel sliding, and was validated by comparing real and simulated behavior. Comparison results reveal the superiority of the sensor fusion proposal under the presence of nonuniform, slow-rate measurements. Full article
(This article belongs to the Special Issue Positioning and Localization in Mobile Robots and Intelligent Transportation Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop