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Advances in Localization and Navigation

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

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 18083

Special Issue Editors


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Guest Editor
Engineering Geodesy, Institute of Geodesy and Geophysics, Vienna University of Technology, 1040 Vienna, Austria
Interests: positioning and navigation with GNSS; location-based services (LBS); indoor and pedestrian navigation; applications of multi-sensor systems
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Guest Editor

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Guest Editor
Unit of Spatial Planning and Regional Development – SPReD, School of Rural and Surveying Engineering, Natonionla Technical University of Athens NTUA., Zographou Campus, 15780 Zografou, Greece
Interests: sensor fusion and Kalman filtering for navigation, engineering surveying and structural deformation monitoring
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Geoinformatics, VŠB – Technical University of Ostrava, 17. listopadu 2172/15, 70800 Ostrava, Czech Republic
Interests: satellite positioning and navigation; GNSS meteorology; location-based services; spatial data collection; remote sensing; unmanned air vehicles; natural hazards
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, the globalized world counts on localized data and location-aware services in a broad list of domains. People use their mobile devices for navigation in day-to-day professional and leisure time activities, companies automate their production or distribution, (unmanned) vehicles autonomously carry out given tasks separately or even cooperatively, and practically everything can be tracked during its movement. Seamless solutions for outdoor and also indoor mapping and navigation are being driven based on diverse technologies and their fusions. Experts in geoinformatics, electronics, and other fields meet in multidisciplinary teams to address new challenges.

This Special Issue, which stems from the conference “GIS Ostrava 2021: Advances in Localization and Navigation”, welcome submissions on methodological or applied aspects focused on (but not limited to) following topics:

  • localization via wireless networks
  • satellite positioning and navigation
  • vision based localization and navigation
  • inertial localization and navigation
  • fusion of sensors and technologies
  • autonomous operation of vehicles and robots
  • simultaneous navigation and mapping (SLAM)
  • cooperative localization and navigation, intelligent transportation
  • artificial intelligence in localization and navigation
  • indoor navigation
  • pedestrian navigation
  • location-based services
  • high-definition maps
  • standards and interoperability
  • algorithms and software development 

Prof. Dr. Ondrej Krejcar
Prof. Dr. Vassilis Gikas
Dr. Guenther Retscher
Dr. Michal Kačmařík
Guest Editors

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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 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

  • positioning
  • navigation
  • sensor fusion
  • satellite positioning
  • vision-based navigation
  • inertial navigation
  • autonomous operation
  • localization and simultaneous localization and mapping (SLAM)
  • indoor navigation
  • location-based services

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Published Papers (6 papers)

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Research

18 pages, 2264 KiB  
Article
A Unified Approach to Spatial Proximity Query Processing in Dynamic Spatial Networks
by Hyung-Ju Cho
Sensors 2021, 21(16), 5258; https://doi.org/10.3390/s21165258 - 4 Aug 2021
Viewed by 1734
Abstract
Nearest neighbor (NN) and range (RN) queries are basic query types in spatial databases. In this study, we refer to collections of NN and RN queries as spatial proximity (SP) queries. At peak times, location-based services (LBS) need to quickly process SP queries [...] Read more.
Nearest neighbor (NN) and range (RN) queries are basic query types in spatial databases. In this study, we refer to collections of NN and RN queries as spatial proximity (SP) queries. At peak times, location-based services (LBS) need to quickly process SP queries that arrive simultaneously. Timely processing can be achieved by increasing the number of LBS servers; however, this also increases service costs. Existing solutions evaluate SP queries sequentially; thus, such solutions involve unnecessary distance calculations. This study proposes a unified batch algorithm (UBA) that can effectively process SP queries in dynamic spatial networks. With the proposed UBA, the distance between two points is indicated by the travel time on the shortest path connecting them. The shortest travel time changes frequently depending on traffic conditions. The goal of the proposed UBA is to avoid unnecessary distance calculations for nearby SP queries. Thus, the UBA clusters nearby SP queries and exploits shared distance calculations for query clusters. Extensive evaluations using real-world roadmaps demonstrated the superiority and scalability of UBA compared with state-of-the-art sequential solutions. Full article
(This article belongs to the Special Issue Advances in Localization and Navigation)
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26 pages, 17292 KiB  
Article
Methodology of Using Terrain Passability Maps for Planning the Movement of Troops and Navigation of Unmanned Ground Vehicles
by Wojciech Dawid and Krzysztof Pokonieczny
Sensors 2021, 21(14), 4682; https://doi.org/10.3390/s21144682 - 8 Jul 2021
Cited by 17 | Viewed by 3692
Abstract
The determination of the route of movement is a key factor which enables navigation. In this article, the authors present the methodology of using different resolution terrain passability maps to generate graphs, which allow for the determination of the optimal route between two [...] Read more.
The determination of the route of movement is a key factor which enables navigation. In this article, the authors present the methodology of using different resolution terrain passability maps to generate graphs, which allow for the determination of the optimal route between two points. The routes are generated with the use of two commonly used pathfinding algorithms: Dijkstra’s and A-star. The proposed methodology allows for the determination of routes in various variants—A more secure route that avoids all terrain obstacles with a wide curve, or a shorter route, which is, however, more difficult to pass. In order to achieve that, two functions that modify the value of the index of passability (IOP), which is assigned to the primary fields that the passability map consists of, have been used. These functions have a β parameter that augments or reduces the impact of the applied function on IOP values. The paper also shows the possibilities of implementation of the methodology for the movement of single vehicles or unmanned ground vehicles (UGVs) by using detailed maps as well as for determining routes for large military operational units moving in a 1 km wide corridor. The obtained results show that the change in β value causes the change of a course of the route as expected and that Dijkstra’s algorithm is more stable and slightly faster than A-star. The area of application of the presented methodology is very wide because, except for planning the movement of unmanned ground vehicles or military units of different sizes, it can be used in crisis management, where the possibility of reaching the area outside the road network can be of key importance for the success of the salvage operation. Full article
(This article belongs to the Special Issue Advances in Localization and Navigation)
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15 pages, 2329 KiB  
Article
Condition-Invariant Robot Localization Using Global Sequence Alignment of Deep Features
by Junghyun Oh, Changwan Han and Seunghwan Lee
Sensors 2021, 21(12), 4103; https://doi.org/10.3390/s21124103 - 15 Jun 2021
Cited by 2 | Viewed by 2385
Abstract
Localization is one of the essential process in robotics, as it plays an important role in autonomous navigation, simultaneous localization, and mapping for mobile robots. As robots perform large-scale and long-term operations, identifying the same locations in a changing environment has become an [...] Read more.
Localization is one of the essential process in robotics, as it plays an important role in autonomous navigation, simultaneous localization, and mapping for mobile robots. As robots perform large-scale and long-term operations, identifying the same locations in a changing environment has become an important problem. In this paper, we describe a robust visual localization system under severe appearance changes. First, a robust feature extraction method based on a deep variational autoencoder is described to calculate the similarity between images. Then, a global sequence alignment is proposed to find the actual trajectory of the robot. To align sequences, local fragments are detected from the similarity matrix and connected using a rectangle chaining algorithm considering the robot’s motion constraint. Since the chained fragments provide reliable clues to find the global path, false matches on featureless structures or partial failures during the alignment could be recovered and perform accurate robot localization in changing environments. The presented experimental results demonstrated the benefits of the proposed method, which outperformed existing algorithms in long-term conditions. Full article
(This article belongs to the Special Issue Advances in Localization and Navigation)
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14 pages, 17667 KiB  
Communication
Speed Control for Leader-Follower Robot Formation Using Fuzzy System and Supervised Machine Learning
by Mohammad Samadi Gharajeh and Hossein B. Jond
Sensors 2021, 21(10), 3433; https://doi.org/10.3390/s21103433 - 14 May 2021
Cited by 17 | Viewed by 3151
Abstract
Mobile robots are endeavoring toward full autonomy. To that end, wheeled mobile robots have to function under non-holonomic constraints and uncertainty derived by feedback sensors and/or internal dynamics. Speed control is one of the main and challenging objectives in the endeavor for efficient [...] Read more.
Mobile robots are endeavoring toward full autonomy. To that end, wheeled mobile robots have to function under non-holonomic constraints and uncertainty derived by feedback sensors and/or internal dynamics. Speed control is one of the main and challenging objectives in the endeavor for efficient autonomous collision-free navigation. This paper proposes an intelligent technique for speed control of a wheeled mobile robot using a combination of fuzzy logic and supervised machine learning (SML). The technique is appropriate for flexible leader-follower formation control on straight paths where a follower robot maintains a safely varying distance from a leader robot. A fuzzy controller specifies the ultimate distance of the follower to the leader using the measurements obtained from two ultrasonic sensors. An SML algorithm estimates a proper speed for the follower based on the ultimate distance. Simulations demonstrated that the proposed technique appropriately adjusts the follower robot’s speed to maintain a flexible formation with the leader robot. Full article
(This article belongs to the Special Issue Advances in Localization and Navigation)
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21 pages, 7442 KiB  
Article
Towards the Development and Verification of a 3D-Based Advanced Optimized Farm Machinery Trajectory Algorithm
by Tomáš Řezník, Lukáš Herman, Martina Klocová, Filip Leitner, Tomáš Pavelka, Šimon Leitgeb, Kateřina Trojanová, Radim Štampach, Dimitrios Moshou, Abdul M. Mouazen, Thomas K. Alexandridis, Jakub Hrádek, Vojtěch Lukas and Petr Širůček
Sensors 2021, 21(9), 2980; https://doi.org/10.3390/s21092980 - 23 Apr 2021
Cited by 10 | Viewed by 2627
Abstract
Efforts related to minimizing the environmental burden caused by agricultural activities and increasing economic efficiency are key contemporary drivers in the precision agriculture domain. Controlled Traffic Farming (CTF) techniques are being applied against soil compaction creation, using the on-line optimization of trajectory planning [...] Read more.
Efforts related to minimizing the environmental burden caused by agricultural activities and increasing economic efficiency are key contemporary drivers in the precision agriculture domain. Controlled Traffic Farming (CTF) techniques are being applied against soil compaction creation, using the on-line optimization of trajectory planning for soil-sensitive field operations. The research presented in this paper aims at a proof-of-concept solution with respect to optimizing farm machinery trajectories in order to minimize the environmental burden and increase economic efficiency. As such, it further advances existing CTF solutions by including (1) efficient plot divisions in 3D, (2) the optimization of entry and exit points of both plot and plot segments, (3) the employment of more machines in parallel and (4) obstacles in a farm machinery trajectory. The developed algorithm is expressed in terms of unified modeling language (UML) activity diagrams as well as pseudo-code. Results were visualized in 2D and 3D to demonstrate terrain impact. Verifications were conducted at a fully operational commercial farm (Rostěnice, the Czech Republic) against second-by-second sensor measurements of real farm machinery trajectories. Full article
(This article belongs to the Special Issue Advances in Localization and Navigation)
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18 pages, 30825 KiB  
Article
Variation of Low-Frequency Time-Code Signal Field Strength during the Annular Solar Eclipse on 21 June 2020: Observation and Analysis
by Xin Wang, Bo Li, Fan Zhao, Xinyu Luo, Luxi Huang, Ping Feng and Xiaohui Li
Sensors 2021, 21(4), 1216; https://doi.org/10.3390/s21041216 - 9 Feb 2021
Cited by 7 | Viewed by 2762
Abstract
Due to the occlusion of the moon, an annular solar eclipse will have an effect on the ionosphere above the earth. The change of the ionosphere, for the low-frequency time-code signal that relies on it as a reflection medium for long-distance propagation, the [...] Read more.
Due to the occlusion of the moon, an annular solar eclipse will have an effect on the ionosphere above the earth. The change of the ionosphere, for the low-frequency time-code signal that relies on it as a reflection medium for long-distance propagation, the signal field strength, and other parameters will also produce corresponding changes, which will affect the normal operation of the low-frequency time-code time service system. This paper selects the solar eclipse that occurred in China on 21 June 2020, and uses the existing measurement equipment to carry out experimental research on the low-frequency time-code signal. We measured and analyzed the signal field strength from 20 June 2020 to 23 June 2020, and combined solar activity data, ionospheric data, and geomagnetic data, and attempted to explore the reasons and rules of the change of signal parameters. The results showed that the field strength of the low-frequency time-code signal changed dramatically within a short time period, the max growth value can reach up to 17 dBμV/m and the variation trend yielded ‘three mutations’. This change in signal field strength is probably due to the occurrence of a solar eclipse that has an effect on the ionosphere. When the signal propagation conditions change, the signal strength will also change accordingly. Full article
(This article belongs to the Special Issue Advances in Localization and Navigation)
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