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Applied Sciences
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Unmanned Systems: Intelligent Perception, Autonomous Navigation, and Positioning
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Unmanned Systems: Intelligent Perception, Autonomous Navigation, and Positioning

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

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1658

Special Issue Editors

Dr. Haoqian Huang

E-Mail Website
Guest Editor
College of Artificial Intelligence and Automation, Hohai University, Changzhou 213200, China
Interests: integrated navigation; filtering; underwater vehicle; intelligent sensor
Special Issues, Collections and Topics in MDPI journals
Dr. Di Wang

E-Mail Website
Guest Editor
College of Artificial Intelligence and Automation, Hohai University, Changzhou 213200, China
Interests: underwater navigation and positioning; underwater robot

Special Issue Information

Dear Colleagues,

Autonomous vehicles (AUV) have difficulty in exploring the unknown environment, such as underwater, air and other areas. To fuse various sensors carried and obtain high-precision information independently is an important issue of environment perception. For example, the underwater environment has the characteristics of poor light conditions, image tone shift, and sensor interference, which is not conducive to the work of autonomous underwater vehicles. Focusing on the positioning and mapping of autonomous underwater vehicles in unknown environment detection, this Special Issue mainly shows intelligent perception, automous navigation and positioning for unmanned systems, which enable them tomore accurately and carefully locate and reconstruct underwater environments.

Dr. Haoqian Huang
Dr. Di Wang
Guest Editors

Manuscript Submission Information

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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.

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Keywords

  • unmanned system
  • environment perception
  • navigation and positioning
  • mapping

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Published Papers (3 papers)

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Research

27 pages, 7306 KB  
Article
Design and Implementation of the AquaMIB Unmanned Surface Vehicle for Real-Time GIS-Based Spatial Interpolation and Autonomous Water Quality Monitoring
by Huseyin Duran and Namık Kemal Sonmez
Appl. Sci. 2026, 16(3), 1209; https://doi.org/10.3390/app16031209 - 24 Jan 2026
Viewed by 113
Abstract
This article introduces the design and implementation of an Unmanned Surface Vehicle (USV), named “AquaMIB”, which introduces a novel and integrated approach for real-time and autonomous water quality monitoring in aquatic environments. The system integrates modular hardware and software, combining sensors for temperature, [...] Read more.
This article introduces the design and implementation of an Unmanned Surface Vehicle (USV), named “AquaMIB”, which introduces a novel and integrated approach for real-time and autonomous water quality monitoring in aquatic environments. The system integrates modular hardware and software, combining sensors for temperature, pH, conductivity, dissolved oxygen, and oxidation reduction potential with GPS, LiDAR, a digital compass, communication modules, and a dedicated power unit. Software components include Python on a Raspberry Pi for navigation and control, C on an Atmega 324P for sensing, C++ on an Arduino Uno for remote control, and C#/JavaScript for the web-based control center. Users assign task points, and the USV autonomously navigates, collects data, and transmits it via RESTful API. Field trials showed 96.5% navigation accuracy over 2.2 km, with 66% of task points reached within 3 m. A total of 120 measurements were processed in real time and visualized as GIS-based spatial maps. The system demonstrates a cost-effective, modular solution for aquatic monitoring. The system’s ability to generate real-time GIS maps enables immediate identification of environmental anomalies, transforming raw sensor data into an actionable decision-support tool for aquatic management. Full article
(This article belongs to the Special Issue Unmanned Systems: Intelligent Perception, Autonomous Navigation, and Positioning)
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25 pages, 761 KB  
Article
Designing a Reference Model for the Deployment of Shared Autonomous Vehicles in Lisbon
by António Pedro Ribeiro Camacho, Miguel Mira da Silva and António Reis Pereira
Appl. Sci. 2026, 16(1), 82; https://doi.org/10.3390/app16010082 - 21 Dec 2025
Viewed by 434
Abstract
Urban mobility in Lisbon faces persistent constraints driven not only by congestion, parking scarcity, and emissions but also by deeper structural issues such as fragmented governance and limited cross-peripheral public transport connectivity. These shortcomings hinder integrated mobility planning and motivate the exploration of [...] Read more.
Urban mobility in Lisbon faces persistent constraints driven not only by congestion, parking scarcity, and emissions but also by deeper structural issues such as fragmented governance and limited cross-peripheral public transport connectivity. These shortcomings hinder integrated mobility planning and motivate the exploration of Shared Autonomous Vehicles (SAVs) as a complementary urban transport solution. Existing SAV frameworks rarely integrate governance coordination, data interoperability, and contextual adaptation for medium-sized European cities. This study addresses this gap by designing and validating a reference model for the deployment of SAVs in Lisbon using a design–science approach combining a literature review, enterprise architecture modelling, and stakeholder validation. The proposed model contributes the following: (i) a governance coordination framework for multi-actor urban mobility ecosystems; (ii) an integrated digital and application architecture supporting multimodal services and user trust mechanisms; and (iii) a technology layer enabling V2X communication and interoperable mobility data flows. The model is demonstrated through Lisbon-specific scenarios aligned with local sustainable mobility strategies. Scenario interpretation is informed by literature-based performance benchmarks—including travel-time reductions of 13–42%, energy-use reductions of 12%, and GHG reductions of 5.6%—which are used as reference indicators rather than simulation outputs. The resulting framework bridges strategic policy and implementable system architecture, supporting the transition towards integrated, sustainable, and autonomous mobility in medium-sized European cities. Full article
(This article belongs to the Special Issue Unmanned Systems: Intelligent Perception, Autonomous Navigation, and Positioning)
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16 pages, 923 KB  
Article
SRNet-Trans: A Singal-Image Guided Depth Completion Regression Network for Transparent Object
by Tao Tao, Hong Zheng, Jinsheng Xiao, Wenfei Wu and Jianfeng Yang
Appl. Sci. 2025, 15(19), 10566; https://doi.org/10.3390/app151910566 - 30 Sep 2025
Viewed by 858
Abstract
Transparent objects are prevalent in various everyday scenarios. However, their reflective and refractive optical properties present significant challenges for conventional optical sensors. This difficulty makes the task of generating dense depth maps from sparse depth maps and high-resolution RGB images a critical area [...] Read more.
Transparent objects are prevalent in various everyday scenarios. However, their reflective and refractive optical properties present significant challenges for conventional optical sensors. This difficulty makes the task of generating dense depth maps from sparse depth maps and high-resolution RGB images a critical area of research. In this paper, we introduce SRNet-Trans, a novel two-stage depth completion framework specifically designed for transparent objects. The approach is structured into two stages, each primarily focused on leveraging semantic and depth information, respectively. In the first stage, RGB images and sparse depth maps are used to predict a relatively dense depth map. The second stage then takes the predicted depth from the first stage, along with the sparse depth map, to generate a final dense depth map. The depth information produced by the two stages is complementary, allowing for effective fusion of both outputs. To enhance the depth estimation process, we integrate a self-attention mechanism in the first stage to better capture semantic features and introduce geometric convolutional layers in the second stage to improve depth encoding accuracy. Additionally, we incorporate a global consistency-based fine depth recovery technique to further refine the final depth map. Extensive experiments on the large-scale real-world TransCG dataset demonstrate that SRNet-Trans outperforms current state-of-the-art methods in terms of depth estimation accuracy. Full article
(This article belongs to the Special Issue Unmanned Systems: Intelligent Perception, Autonomous Navigation, and Positioning)
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