Enhancing Underwater Navigation, Localization, and Path Planning for Marine Robotics: Advances and Challenges

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 930

Special Issue Editors


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Guest Editor
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
Interests: underwater acoustic signal processing; underwater acoustic propagation; underwater localization

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Guest Editor
Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
Interests: underwater acoustic communication; underwater acoustic positioning; underwater PNT (positioning, navigation, and timing); underwater navigation systems
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Special Issue Information

Dear Colleagues,

Underwater navigation, localization, and path planning are foundational technologies for marine robotic systems, including remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs). These enable the use of these vehicles in critical applications such as environmental monitoring, subsea infrastructure inspection, and deep-sea exploration, particularly in challenging environments characterized by harsh oceanic conditions or partial prior knowledge. Despite technological progress in this area, persistent challenges, including acoustic communication constraints, dynamic model inaccuracies, and environmental uncertainties, continue to impede system reliability. Addressing these limitations is paramount to advancing the operational efficiency, autonomy, and intelligent decision-making of underwater robotic platforms.

This Special Issue seeks original research contributions and comprehensive reviews addressing theoretical innovations and the practical implementation of underwater navigation systems. We particularly welcome interdisciplinary approaches that bridge the gaps between traditional methodologies and emerging computational paradigms. Topics of interest include, but are not limited to, the following:

  • Integrated Navigation Architectures: Sensor fusion techniques for inertial navigation systems (INSs), Doppler Velocity Logs (DVLs), and sonar-based positioning.
  • Acoustic Signal Processing: Advanced algorithms for underwater communication and target detection in noisy environments.
  • Adaptive Path Planning: Machine learning-driven strategies for dynamic obstacle avoidance and energy-optimal trajectory generation.
  • Resilient Localization: Real-time SLAM implementations and probabilistic frameworks for uncertainty quantification.
  • Intelligent Control Systems: Model predictive control and bio-inspired navigation paradigms.

Submissions should present a rigorous theoretical analysis coupled with experimental validation through field trials or high-fidelity simulations. We encourage contributions that highlight novel sensor modalities, edge computing implementations, and the cross-domain applications of AI/ML techniques to push the boundaries of marine robotic autonomy.

Dr. Bo Lei
Prof. Dr. Tongwei Zhang
Guest Editors

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Keywords

  • multi-sensor fusion and measurement
  • acoustic navigation
  • LBL/SBL/USBL
  • SLAM and sonar-based localization
  • collaborative localization
  • artificial neural networks
  • motion planning
  • communication systems
  • navigation and guidance systems
  • intelligent control and automation systems

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Published Papers (1 paper)

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Research

17 pages, 9764 KiB  
Article
Depth Estimation of an Underwater Moving Source Based on the Acoustic Interference Pattern Stream
by Lintai Rong, Bo Lei, Tiantian Gu and Zhaoyang He
Electronics 2025, 14(11), 2228; https://doi.org/10.3390/electronics14112228 - 30 May 2025
Viewed by 420
Abstract
For a bottom-moored vertical line array in deep ocean, the underwater maneuvering source will produce interference patterns in both grazing angle–distance (vertical-time record, VTR) and frequency–grazing angle (wideband beamforming output) domains, respectively, and the interference period is modulated by the source depth. Based [...] Read more.
For a bottom-moored vertical line array in deep ocean, the underwater maneuvering source will produce interference patterns in both grazing angle–distance (vertical-time record, VTR) and frequency–grazing angle (wideband beamforming output) domains, respectively, and the interference period is modulated by the source depth. Based on these characteristics, an interference feature fusion (IFF) method is proposed in the space–time–frequency domain for source depth estimation, in which the principal interference mode of the VTR is extracted adaptively and the depth ambiguity function is constructed by fusing the ambiguity sequence, mapped by wideband beamforming intensity, and the principal interference mode, which can achieve the long-term depth estimation and recognition of underwater sources without requiring environmental information. Theoretical analysis and simulation results indicate that the IFF can suppress the false peaks generated by the generalized Fourier transform (GFT) method, and the depth estimation error of the IFF for a single source is reduced by at least 47% compared to GFT. In addition, the IFF is proven to be effective at separating the depth of multiple adjacent sources (with the average estimation error reduced by 28%) and exhibits a high degree of robustness within the fluctuating acoustic channel (with the average estimation error reduced by 12%). Full article
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