A review of terrain aided navigation for underwater vehicles

Ma, Teng; Ding, Shuoshuo; Li, Ye; Fan, Jiajia

doi:10.1016/j.oceaneng.2023.114779

Cited by 13 publications

(3 citation statements)

References 76 publications

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“…Billings et al. [ 71 ] proposed a visual feature-based method with robust mapping capability in the seafloor environments. The method successfully fuses the features from both a body stereo camera and a manipulator fisheye camera.…”

Section: Key Technologies Of the Uvmsmentioning

confidence: 99%

Underwater Robots and Key Technologies for Operation Control

Sun,

Wang,

Hui

et al. 2024

Cyborg Bionic Syst

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Over time, the utilization of the Underwater Vehicle-Manipulator System (UVMS) has steadily increased in exploring and harnessing marine resources. However, the underwater environment poses big challenges for controlling, navigating, and communicating with UVMS. These challenges have not only spurred the continuous advancement of related technologies, but also made the development of the UVMS even more captivating. This article firstly provides a review of development status of the UVMS and discusses the current limitations and future directions, and then reviews in detail the dynamic and hydrodynamic modeling methods, and analyzes the principles, advantages, and disadvantages of various approaches. Then, we try to review 2 key technologies of operation control methods, including underwater positioning and navigation technologies and vehicle-manipulator coordinated control approaches. Finally, a reasonable prospect for the future development of UVMS is given.

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Section: Key Technologies Of the Uvmsmentioning

confidence: 99%

Underwater Robots and Key Technologies for Operation Control

Sun,

Wang,

Hui

et al. 2024

Cyborg Bionic Syst

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“…The merging of SLAM with XR technologies indicates a growing new area of improving spatial awareness, interactive experiences, and developing highly immersive digital environments. Moreover, the incorporation of control and estimation methods into many area [15][16][17][18][19][20][21][22][23][24][25][26][27][28], including into SLAM algorithms further enhances accuracy and reliability in dynamic environments, bridging the gap between theoretical modeling and real-world applications [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. The progression of SLAM, starting with its basic algorithms and extending to its use in XR, signifies a crucial moment in the story of computer sciences and human-computer interaction [45][46][47][48][49][50][51][52][53].…”

Section: Introductionmentioning

confidence: 99%

SLAM in XR: a bibliometric analysis of its application in virtual, augmented, and mixed reality

Obaideen,

AlShabi

2024

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI

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The growing sector of Extended Reality (XR), comprising Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), requires successful approaches for localization and mapping. Simultaneous Localization and Mapping (SLAM) has gained more importance in XR uses. This research conducts an in-depth bibliometric examination of the utilization of SLAM in XR settings, analyzing publications from the last ten years. We investigate the developing trends, fields of knowledge, prominent contributors, and important publications that have influenced this intersection. Our study indicates a notable increase in research on incorporating SLAM in XR, especially in fields such as gaming, architectural visualization, and remote collaboration. A study of the region highlights North America and the Asia-Pacific as key players in this field of research. The research also discusses the difficulties involved in integrating SLAM into XR, such as handling the computational requirements, guaranteeing real-time processing, and accomplishing successful sensor fusion. This paper strives to provide a thorough overview of the current status of SLAM in XR, pinpointing gaps that already exist and suggesting directions for further research. These observations aim to help researchers, developers, and industry professionals who want to use SLAM's capabilities in the quickly changing XR field.

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“…Navigation and positioning systems are the core technologies of autonomous underwater vehicles (AUVs) [1,2]. However, due to the rapid attenuation of Global Positioning System (GPS) signals in water, autonomous underwater robots cannot rely on GPSs for accurate navigation and positioning [3,4].…”

Section: Introductionmentioning

confidence: 99%

Underwater Geomagnetic Localization Based on Adaptive Fission Particle-Matching Technology

Yu,

Li,

Yang

et al. 2023

JMSE

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The geomagnetic field constitutes a massive fingerprint database, and its unique structure provides potential position correction information. In recent years, particle filter technology has received more attention in the context of robot navigation. However, particle degradation and impoverishment have constrained navigation systems’ performance. This paper transforms particle filtering into a particle-matching positioning problem and proposes a geomagnetic localization method based on an adaptive fission particle filter. This method employs particle-filtering technology to construct a geomagnetic matching positioning model. Through adaptive particle fission and sampling, the problem of particle degradation and impoverishment in traditional particle filtering is solved, resulting in improved geomagnetic matching positioning accuracy. Finally, the proposed method was tested in a sea trial, and the results show that the proposed method has a lower positioning error than traditional particle-filtering and intelligent particle-filtering algorithms. Under geomagnetic map conditions, an average positioning accuracy of about 546.44 m is achieved.

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A review of terrain aided navigation for underwater vehicles

Cited by 13 publications

References 76 publications

Underwater Robots and Key Technologies for Operation Control

Underwater Robots and Key Technologies for Operation Control

SLAM in XR: a bibliometric analysis of its application in virtual, augmented, and mixed reality

Underwater Geomagnetic Localization Based on Adaptive Fission Particle-Matching Technology

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