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LIDAR Applications in Mobile Robots
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LIDAR Applications in Mobile Robots

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 749

Special Issue Editor

Prof. Dr. Jordi Palacín Roca

E-Mail Website
Guest Editor
Laboratory of Robotics, Universitat de Lleida, Jaume II 69, 25001 Lleida, Spain
Interests: mobile robots; omnidirectional mobile robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

LIDAR sensors are currently playing an important role in the rising popularity and increasing complexity of mobile robots. The evolution of LIDAR sensors has led to, in some cases, a new mobile robot application being simply a new LIDAR application implemented in a mobile device in which the information gathered from LIDAR is not restricted to classical concepts such as positioning, mapping, navigation, and environmental modeling. This growing evolution will lead to the development of new sensor models, methods, algorithms, and techniques for real-world single and multi-sensor LIDAR applications.

The aim of this Special Issue is to present current and state­-of-the-art research in LIDAR applications in mobile robots, highlighting the development of new sensing concepts and processing methodologies. This Special Issue welcomes contributions exploring, but not limited to, the following topics:

  • New LIDAR sensing solutions for mobile robots.
  • Integration of multiple LIDARS in mobile robots.
  • Mobile robot applications based on low-cost LIDARs.
  • Extracting information from LIDAR embedded in mobile robots.
  • Alternative LIDAR applications for mobile robot self-localization and mapping.

Prof. Dr. Jordi Palacín Roca
Guest 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 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. 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 2600 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

  • LIDAR
  • multi-sensor
  • sensor calibration
  • mobile robot
  • real world

Published Papers (1 paper)

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Research

14 pages, 3080 KiB  
Article
Online Calibration of Extrinsic Parameters for Solid-State LIDAR Systems
by Mark O. Mints, Roman Abayev, Nick Theisen, Dietrich Paulus and Anselm von Gladiss
Sensors 2024, 24(7), 2155; https://0-doi-org.brum.beds.ac.uk/10.3390/s24072155 - 27 Mar 2024
Viewed by 421
Abstract
This work addresses the challenge of calibrating multiple solid-state LIDAR systems. The study focuses on three different solid-state LIDAR sensors that implement different hardware designs, leading to distinct scanning patterns for each system. Consequently, detecting corresponding points between the point clouds generated by [...] Read more.
This work addresses the challenge of calibrating multiple solid-state LIDAR systems. The study focuses on three different solid-state LIDAR sensors that implement different hardware designs, leading to distinct scanning patterns for each system. Consequently, detecting corresponding points between the point clouds generated by these LIDAR systems—as required for calibration—is a complex task. To overcome this challenge, this paper proposes a method that involves several steps. First, the measurement data are preprocessed to enhance its quality. Next, features are extracted from the acquired point clouds using the Fast Point Feature Histogram method, which categorizes important characteristics of the data. Finally, the extrinsic parameters are computed using the Fast Global Registration technique. The best set of parameters for the pipeline and the calibration success are evaluated using the normalized root mean square error. In a static real-world indoor scenario, a minimum root mean square error of 7 cm was achieved. Importantly, the paper demonstrates that the presented approach is suitable for online use, indicating its potential for real-time applications. By effectively calibrating the solid-state LIDAR systems and establishing point correspondences, this research contributes to the advancement of multi-LIDAR fusion and facilitates accurate perception and mapping in various fields such as autonomous driving, robotics, and environmental monitoring. Full article
(This article belongs to the Special Issue LIDAR Applications in Mobile Robots)
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