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Special Issue "Recent Advances in Unmanned System Navigation and Control"

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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: 30 April 2023 | Viewed by 3227

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Special Issue Editors

Prof. Dr. Lihui Wang

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Guest Editor

School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
Interests: unmanned system navigation and control; precision sensing; computer vision; intelligent algorithm

Dr. Chen Wang

E-Mail Website
Guest Editor

National Engineering Research Center of Software Engineering, Peking University, Beijing 100871, China
Interests: unmanned underwater system; bionic perception and control; biomimetic robotics; multi-robot systems

Prof. Dr. Yonggang Zhang
E-Mail Website
Guest Editor

College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
Interests: inertial navigation; integrated navigation and information fusion

Special Issue Information

Dear Colleagues,

Navigation and control are fundamental to certain unmanned vehicles, such as aircrafts, ships, and submersibles. During complicated events, None-GNSS information and other complex situations, the need to achieve autonomous navigation and control has become more urgent. In recent years, based on inertial navigation, intelligent autonomous navigation and control technology that integrates artificial intelligence, vision, lasers, millimeter waves and acoustic waves, geophysical fields and other forms of technology have played an important role in unmanned system navigation, environmental perception and situational awareness.

The current Special Issue, "Recent Advances in Unmanned System Navigation and Control", addresses innovative forms of technology, such as environmental perception and understanding, real-time accurate autonomous positioning and intelligent navigation in complex scenarios. In the development and trends of autonomous navigation, visual navigation, laser navigation, geophysical field navigation, SLAM, navigation feature modeling, navigation map construction, target tracking algorithm and multi-sensor fusion algorithm, these forms of technology have been used to conduct the related key discussions on technology. This Special Issue contributes to the research concerning the autonomous navigation and control of unmanned systems. We invite submissions of studies that address these topics.

The current Special Issue includes topics on, but not limited to, the following areas:

Environmental perception;
Simultaneous localization and mapping;
Visual-based navigation;
Laser-based navigation;
Geophysical field-based navigation;
Cooperative navigation;
Navigation feature modeling;
Navigation map construction;
Target tracking;
Tracking of dynamic targets;
Three-dimensional mapping;
Multi-sensor fusion.

Prof. Dr. Lihui Wang
Dr. Chen Wang
Prof. Dr. Yonggang Zhang
Guest Editors

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. Electronics 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 2000 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

unmanned aerial vehicle (UAV)
unmanned vehicle
visual navigation
laser navigation
geophysical field navigation
SLAM
navigation feature modeling
three-dimensional mapping
target tracking
multi-sensor fusion

Published Papers (4 papers)

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Research

Open AccessArticle

FIImap: Fast Incremental Inflate Mapping for Autonomous MAV Navigation

and

Electronics 2023, 12(3), 534; https://doi.org/10.3390/electronics12030534 - 20 Jan 2023

Viewed by 755

Abstract

Three-dimensional mapping is an essential component of autonomous Micro Aerial Vehicle (MAV) navigation. The paper focuses on the 3D spatial representation method of MAV to overcome the collision problem caused by soft constraints, control error, and planning with the center of mass by inflating the occupancy grid map. A fast incremental inflated map construction method is proposed, which reduces the time-consumption caused by the increase of map range and inflated size. The method focuses on areas of the map that occupied state changes and introduces two arrays that record newly appearing and disappearing obstacles. Then, a series of breadth-first search algorithms are used to traverse the parts of the inflated map that need local modification to update the inflated map. Moreover, a sliding map model is designed based on the MAV position, which is suitable for large-range autonomous flight. The effectiveness of the proposed approach is verified with simulated and actual flight data. The proposed method takes about 3 ms to construct the inflated map with a local update range of 16 m × 16 m × 6 m. Full article

(This article belongs to the Special Issue Recent Advances in Unmanned System Navigation and Control)

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Open AccessArticle

Cooperative Following of Multiple Autonomous Robots Based on Consensus Estimation

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Electronics 2022, 11(20), 3319; https://doi.org/10.3390/electronics11203319 - 14 Oct 2022

Viewed by 479

Abstract

When performing a specific task, a Multi-Agent System (MAS) not only needs to coordinate the whole formation but also needs to coordinate the dynamic relationship among all the agents, which means judging and adjusting their positions in the formation according to their location, velocity, surrounding obstacles and other information to accomplish specific tasks. This paper devises an integral separation feedback method for a single-agent control with a developed robot motion model; then, an enhanced strategy incorporating the dynamic information of the leader robot is proposed for further improvement. On this basis, a method of combining second-order formation control with path planning is proposed for multiple-agents following control, which uses the system dynamic of one agent and the Laplacian matrix to generate the consensus protocol. Due to a second-order consensus, the agents exchange information according to a pre-specified communication digraph and keep in a certain following formation. Moreover, an improved path planning method using an artificial potential field is developed to guide the MAS to reach the destination and avoid collisions. The effectiveness of the proposed approach is verified with simulation results in different scenarios. Full article

(This article belongs to the Special Issue Recent Advances in Unmanned System Navigation and Control)

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Open AccessFeature PaperArticle

Analysis of Optimal Operation of Charging Stations Based on Dynamic Target Tracking of Electric Vehicles

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Electronics 2022, 11(19), 3175; https://doi.org/10.3390/electronics11193175 - 02 Oct 2022

Viewed by 673

Abstract

In view of the large impact of traditional charging stations on the power grid and the investment in the construction of charging stations for electric vehicle infrastructure services, this paper considers the configuration of optical storage equipment in charging stations from a practical point of view and proposes an economic operation strategy for charging stations to meet the economically optimal requirements of different scenarios. First, we analyze the behavioral characteristics of multiple types of electric vehicles, consider the influence of charging queues, and establish a daily load model of charging stations by taking into account the daily monitoring load and nighttime lighting load of charging stations. Then, considering the electric vehicle (EV) charging demand, photovoltaic (PV) output and energy storage charging and discharging power, the daily economic optimal operation problem based on the dynamic target tracking of charging stations is established; the objective is to maximize the daily operating revenue of charging stations under the condition of satisfying the EV charging demand and PV consumption. Secondly, the objective function is linearized, and the economic operation model is transformed into a mixed integer linear programming model for solving, and the simulation is verified under different scenarios. The results show that the economic optimal operation strategy can adapt to the economic operation requirements of charging stations in different scenarios and maximize the charging station revenue. Full article

(This article belongs to the Special Issue Recent Advances in Unmanned System Navigation and Control)

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Open AccessArticle

A Novel Hybrid Method Based on Deep Learning for an Integrated Navigation System during DVL Signal Failure

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Electronics 2022, 11(19), 2980; https://doi.org/10.3390/electronics11192980 - 20 Sep 2022

Cited by 2 | Viewed by 597

Abstract

The navigation performance of an autonomous underwater vehicle (AUV) as the main tool for exploring the ocean greatly affects its work efficiency. Under the circumstance that high-precision GNSS positioning signals cannot be obtained, the role of the Strapdown Inertial Navigation System/Doppler Velocity Log (SINS/DVL) integrated navigation system is becoming more prominent. Due to marine creatures or the seafloor topography, DVL is prone to outliers or even failures during measurement. To solve these problems, a LSTM/SVR-VBAKF algorithm aided integrated navigation system is proposed. First, under normal circumstances of DVL, the output information of SINS and DVL are used as training samples, and they train the Long Short-Term Memory (LSTM) model. To enhance the robustness and adaptability of the filter, a novel variational Bayesian adaptive filtering algorithm based on support vector regression is proposed. When the DVL formation is missing, the deep learning method adopted in this paper will be continuously output to ensure the effect of integrated navigation. The shipboard test data is verified from two aspects: filter performance and neural network-assisted integrated navigation system capability. The experimental results show that the new method proposed in this paper can effectively handle a situation where DVL output is not available. Full article

(This article belongs to the Special Issue Recent Advances in Unmanned System Navigation and Control)

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Special Issue "Recent Advances in Unmanned System Navigation and Control"

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