UKF-Based Inverted Ultra-Short Baseline SLAM With Current Compensation

Luo, Jingxin; Ko, Hak-Lim

doi:10.1109/access.2022.3185752

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…Aiming at the underwater feature-poor environments, Negre et al. [ 95 ] proposed a method with a novel loop-closure detection approach, which could effectively reduce the computational effort and system resource consumption without reducing the positioning accuracy. Billings et al.…”

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

View full text Add to dashboard Cite

show abstract

“…As mentioned above, the Kalman filter and its variants are the estimation algorithms that have most frequently been employed to solve SLAM [6]. Nevertheless, Kalman-type filters suffer from some serious shortcomings; for example, their performance depends on the prior information regarding noise statistics and initial values; consistency is also an issue [7].…”

Section: B Literature Reviewmentioning

confidence: 99%

“…In this experiment, the proposed and smooth observers are evaluated on V2_01_easy of EuRoc public dataset. The estimated trajectories of the observers and their comparisons against the ground truth, (which is acquired via a Vicon 6D motion capture system at a rate of 100 Hz) are demonstrated in Figure (6). It is worth noting that the observer-estimated trajectory has been aligned to the ground truth utilizing the Umeyama technique [40].…”

Section: ) First Experimentsmentioning

confidence: 99%

Global Asymptotic Convergent Observer for SLAM

Hashemi

Mattila

2022

IEEE Access

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This paper examines the global convergence problem of SLAM algorithms, an issue that faces topological obstructions. This is because the state-space for attitude kinematics is defined on a noncontractible manifold: the special orthogonal group of order three SO(3). Therefore, this paper presents a novel, gradient-based hybrid observer to overcome these topological obstacles. Moreover, the integral action is applied into the proposed observer to estimate unknown constant bias, which results in an increase in bias estimation. Accordingly, a new projection scheme is defined to cope with the integral action. The Lyapunov stability theorem is used to prove the globally asymptotic convergence of the proposed algorithm. Experimental and simulation results are provided to evaluate the performance and to demonstrate the effectiveness and robustness of the proposed scheme.

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Adaptive Visual-Inertial Odometry Using SuperGlue and Dynamic EKF with Information-Based Confidence Estimation

ASIL,

Nasibov

2024

Preprint

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This study presents an innovative Visual-Inertial Odometry (VIO) approach for Unmanned Aerial Vehicles (UAVs). The proposed system integrates the modern deep learning-based SuperGlue algorithm with an information based adaptive Extended Kalman Filter (EKF). The system establishes a dynamic confidence estimation mechanism using image entropy, intensity variation, and motion blur metrics, thereby providing robust pose estimation even in challenging environmental conditions. Thanks to the superior performance of advanced transformer-based feature matching methods like SuperGlue, the proposed loosely-coupled sensor fusion technique approaches the accuracy of traditional tightly-coupled approaches, potentially offering an alternative to these methods. Comprehensive experiments conducted on the EuRoC MAV dataset demonstrate that the proposed method provides significant improvements compared to conventional approaches. Particularly in challenging scenarios, an improvement of approximately 50% was observed in the estimation of quaternions and Euler angles. This study reveals that loosely-coupled sensor fusion, when combined with advanced feature matching techniques and adaptive filtering strategies, can offer a robust alternative to tightly-coupled approaches. The results highlight the potential applications of the proposed method in fields such as robotic navigation, autonomous vehicles, and augmented reality. Additionally, the Python code associated with our study has been shared as open-source on GitHub for use in other academic studies at "\href{https://github.com/ufukasia/Adaptive-VIO-Odometry}{https://github.com/ufukasia/Adaptive-VIO-Odometry}".

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UKF-Based Inverted Ultra-Short Baseline SLAM With Current Compensation

Cited by 4 publications

References 23 publications

Underwater Robots and Key Technologies for Operation Control

Underwater Robots and Key Technologies for Operation Control

Global Asymptotic Convergent Observer for SLAM

Adaptive Visual-Inertial Odometry Using SuperGlue and Dynamic EKF with Information-Based Confidence Estimation

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