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Novel Technologies in Navigation and Control

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

Deadline for manuscript submissions: closed (20 June 2025) | Viewed by 599

Special Issue Editors

Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Interests: observer-navigation algorithm; nonlinear control system; robotic systems
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Guest Editor Assistant
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Interests: dynamics; control; flight simulation

Special Issue Information

Dear Colleagues,

In recent years, unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) have gained significant momentum among researchers and industries. Applications such as surveillance, infrastructure inspection, delivery, or search-and-rescue greatly benefit from the time and cost efficiency of the robotic platforms. In this context, the aim of the present proposal is to address the problem of autonomous and safe robot navigation and control, which are necessary functions to perform each of the tasks described above. As the extensive literature testifies, the exploration of solutions to realize autonomous navigation and control is still an open and evolving challenge, particularly in the light of contemporary fast-paced technological development. Indeed, the cost-effectiveness of the onboard sensors and the increase in the available computational power make it possible to realize efficient strategies for accurate localization, target estimation, precise path following, and decentralized control.

This Special Issue will explore such topics by collecting papers and reviews focusing on the most recent advances regarding the following fields:

  • Task decentralization and consensus-based control;
  • Distributed filtering for target detection;
  • Flocking, collaborative path planning and collision avoidance;
  • Disturbance rejection and robust control;
  • Multi-sensor fusion and GPS-denied navigation;
  • Wind, ground- and wall-effect estimation;
  • Machine learning-based navigation and control;
  • Adaptive, optimal and robust control;
  • Coordinated navigation and control of formations and swarms;
  • Control under vehicle, operational and actuation constraints.

Dr. Elisa Capello
Guest Editor

Dr. Mauro Mancini
Guest Editor Assistant

Manuscript Submission Information

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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

  • UAV applications
  • control of multi-agent systems
  • path planning and collision avoidance
  • distributed estimation algorithms

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Published Papers (1 paper)

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Research

23 pages, 44747 KiB  
Article
Error Model for Autonomous Global Positioning Method Using Polarized Sky Light and True North Measurement Instrument
by Yinlong Wang, Jinshan Li, Yi Luo and Jinkui Chu
Appl. Sci. 2025, 15(13), 7287; https://doi.org/10.3390/app15137287 - 27 Jun 2025
Viewed by 117
Abstract
Long-distance navigation requires global positioning methods to have complete autonomy, particularly when the Global Positioning System is unavailable. Considering that bionic polarized light-based global positioning technology exhibits good autonomy, this study develops an error model for autonomous global positioning based on the polarized [...] Read more.
Long-distance navigation requires global positioning methods to have complete autonomy, particularly when the Global Positioning System is unavailable. Considering that bionic polarized light-based global positioning technology exhibits good autonomy, this study develops an error model for autonomous global positioning based on the polarized skylight and a true north measurement instrument, using an approach of partial derivatives. The proposed model can rapidly and accurately provide the global error distribution of a bionic positioning method under varying angular measurement errors at different times. In addition, the conditions under which the proposed error model remains valid are investigated. The results indicate that the investigation can be simplified to verify whether the denominators of four partial derivatives of an implicit function system are simultaneously non-zero. The accuracy of the proposed error model is verified through numerical simulations. The results indicate that when the deviations of the two independent variables are up to 0.0001°, the positioning error mostly remains less than 14 m. In contrast, fewer geographical locations have positioning errors approaching positive infinity. By analyzing the global error distribution, one can effectively design and optimize the parameters of the autonomous global positioning system, enhancing its reliability and stability. Full article
(This article belongs to the Special Issue Novel Technologies in Navigation and Control)
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