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Topical Collection "Practical Application of Sensors and Signal Processing Techniques in Mobile Robots"

A topical collection in Sensors (ISSN 1424-8220). This collection belongs to the section "Sensors and Robotics".

Editor

Dr. Jordi Palacín Roca
E-Mail Website
Collection Editor
Laboratory of Robotics, Universitat de Lleida, Jaume II 69, 25001 Lleida, Spain
Interests: mobile robots; omnidirectional mobile robots

Topical Collection Information

Dear Colleagues,

The expectation in the field of mobile robots is the continuous revision and improvement of the classical designs and the development of new breakthrough ideas and concepts ready to implement new functionalities and applications in a highly unstructured real world. The application of sensors and signal processing techniques either as a part of a mobile robot or as a fundamental part of a device of a mobile robot is driving this continuous evolution.

In this direction, the aim of this Topical Collection is to highlight new advances in the field of mobile robots based, directly or indirectly, on the application of sensing concepts and methodologies.

Dr. Jordi Palacín Roca
Collection Editor

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 collection 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. Sensors 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 2200 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

  • Application of sensors in mobile robots
  • New sensors for mobile robots
  • New compact devices for mobile robots
  • Application of signal processing techniques in mobile robots
  • Practical applications of mobile robots
  • Evaluation of mobile robot performances
  • Improvement in mobile robot performances

Published Papers (2 papers)

2021

Article
Three-Dimensional Outdoor Analysis of Single Synthetic Building Structures by an Unmanned Flying Agent Using Monocular Vision
Sensors 2021, 21(21), 7270; https://doi.org/10.3390/s21217270 - 01 Nov 2021
Viewed by 291
Abstract
An algorithm designed for analysis and understanding a 3D urban-type environment by an autonomous flying agent, equipped only with a monocular vision, is presented. The algorithm is hierarchical and is based on the structural representation of the analyzed scene. Firstly, the robot observes [...] Read more.
An algorithm designed for analysis and understanding a 3D urban-type environment by an autonomous flying agent, equipped only with a monocular vision, is presented. The algorithm is hierarchical and is based on the structural representation of the analyzed scene. Firstly, the robot observes the scene from a high altitude to build a 2D representation of a single object and a graph representation of the 2D scene. The 3D representation of each object arises as a consequence of the robot’s actions, as a result of which it projects the object’s solid on different planes. The robot assigns the obtained representations to the corresponding vertex of the created graph. The algorithm was tested by using the embodied robot operating on the real scene. The tests showed that the robot equipped with the algorithm was able not only to localize the predefined object, but also to perform safe, collision-free maneuvers close to the structures in the scene. Full article
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Figure 1

Article
Evaluation of the Path-Tracking Accuracy of a Three-Wheeled Omnidirectional Mobile Robot Designed as a Personal Assistant
Sensors 2021, 21(21), 7216; https://doi.org/10.3390/s21217216 - 29 Oct 2021
Viewed by 331
Abstract
This paper presents the empirical evaluation of the path-tracking accuracy of a three-wheeled omnidirectional mobile robot that is able to move in any direction while simultaneously changing its orientation. The mobile robot assessed in this paper includes a precise onboard LIDAR for obstacle [...] Read more.
This paper presents the empirical evaluation of the path-tracking accuracy of a three-wheeled omnidirectional mobile robot that is able to move in any direction while simultaneously changing its orientation. The mobile robot assessed in this paper includes a precise onboard LIDAR for obstacle avoidance, self-location and map creation, path-planning and path-tracking. This mobile robot has been used to develop several assistive services, but the accuracy of its path-tracking system has not been specifically evaluated until now. To this end, this paper describes the kinematics and path-planning procedure implemented in the mobile robot and empirically evaluates the accuracy of its path-tracking system that corrects the trajectory. In this paper, the information gathered by the LIDAR is registered to obtain the ground truth trajectory of the mobile robot in order to estimate the path-tracking accuracy of each experiment conducted. Circular and eight-shaped trajectories were assessed with different translational velocities. In general, the accuracy obtained in circular trajectories is within a short range, but the accuracy obtained in eight-shaped trajectories worsens as the velocity increases. In the case of the mobile robot moving at its nominal translational velocity, 0.3 m/s, the root mean square (RMS) displacement error was 0.032 m for the circular trajectory and 0.039 m for the eight-shaped trajectory; the absolute maximum displacement errors were 0.077 m and 0.088 m, with RMS errors in the angular orientation of 6.27° and 7.76°, respectively. Moreover, the external visual perception generated by these error levels is that the trajectory of the mobile robot is smooth, with a constant velocity and without perceiving trajectory corrections. Full article
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Figure 1

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