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学者姓名：闫帅铮
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Abstract ：
In this article, we propose a tightly coupled visual-inertial-acoustic sensor fusion method to improve the autonomous localization accuracy of underwater vehicles. To address the performance degradation encountered by existing visual or visual-inertial simultaneous localization and mapping systems when applied in underwater environments, we integrate the Doppler velocity log (DVL), an acoustic velocity sensor, to provide additional motion information. To fully leverage the complementary characteristics among visual, inertial, and acoustic sensors, we perform multimodal information fusion in both frontend tracking and backend mapping processes. Specifically, in the frontend tracking process, we first predict the vehicle's pose using the angular velocity measurements from the gyroscope and linear velocity measurements from the DVL. Thereafter, measurements performed by the three sensors between adjacent camera frames are utilized to construct visual reprojection error, inertial error, and DVL displacement error, which are jointly minimized to obtain a more accurate pose estimation at the current frame. In the backend mapping process, we utilize gyroscope and DVL measurements to construct relative pose change residuals between keyframes, which are minimized together with visual and inertial residuals to further refine the poses of the keyframes within the local map. Experimental results on both simulated and real-world underwater datasets demonstrate that the proposed fusion method improves the localization accuracy by more than 30% compared to the current state-of-the-art ORB-SLAM3 stereo-inertial method, validating the potential of the proposed method in practical underwater applications.
Keyword ：
Accuracy Accuracy Acoustic measurements Acoustic measurements Acoustics Acoustics Acoustic sensors Acoustic sensors Autonomous localization Autonomous localization biomimetic underwater vehicles biomimetic underwater vehicles Cameras Cameras Location awareness Location awareness sensor fusion sensor fusion simultaneous localization and mapping simultaneous localization and mapping State estimation State estimation Underwater vehicles Underwater vehicles Velocity measurement Velocity measurement Visualization Visualization
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| GB/T 7714 | Huang, Yupei , Li, Peng , Ma, Shaoxuan et al. Visual-Inertial-Acoustic Sensor Fusion for Accurate Autonomous Localization of Underwater Vehicles [J]. | IEEE TRANSACTIONS ON CYBERNETICS , 2024 , 55 (2) : 880-896 . |
| MLA | Huang, Yupei et al. "Visual-Inertial-Acoustic Sensor Fusion for Accurate Autonomous Localization of Underwater Vehicles" . | IEEE TRANSACTIONS ON CYBERNETICS 55 . 2 (2024) : 880-896 . |
| APA | Huang, Yupei , Li, Peng , Ma, Shaoxuan , Yan, Shuaizheng , Tan, Min , Yu, Junzhi et al. Visual-Inertial-Acoustic Sensor Fusion for Accurate Autonomous Localization of Underwater Vehicles . | IEEE TRANSACTIONS ON CYBERNETICS , 2024 , 55 (2) , 880-896 . |
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Abstract ：
This article proposes a tightly coupled visual-acoustic sensor fusion method for self-localization of a biomimetic robotic shark. To address the decreased localization accuracy of visual-based simultaneous localization and mapping systems employed on a robotic fish in underwater environments, we integrate velocity measurements from the acoustic sensor Doppler velocity log (DVL) into a visual odometry. To fully exploit the local position change information contained in velocity measurements, DVL measurements are fused in two stages of visual tracking. Specifically, we first employ the velocity measurements to improve the initial camera pose estimation during visual tracking, aiming to provide a better initial value for subsequent pose optimization. Thereafter, these velocity measurements are directly employed to constrain the camera position change between two adjacent frames by constructing a DVL residual term, which is optimized jointly with the visual residual to obtain a more accurate camera pose. Extensive experiments are conducted on both self-collected simulated datasets and real-world underwater datasets. Experimental results demonstrate that the proposed visual-acoustic fusion method can effectively improve the localization accuracy for the robotic shark by more than 50% compared to a pure visual system, providing valuable guidance for improving the autonomous localization capability of underwater biomimetic robots.
Keyword ：
Robotic fish Robotic fish sensor fusion sensor fusion simultaneous localization and mapping (SLAM) simultaneous localization and mapping (SLAM) underwater self-localization underwater self-localization
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| GB/T 7714 | Huang, Yupei , Li, Peng , Yan, Shuaizheng et al. Self-Localization of a Biomimetic Robotic Shark Using Tightly Coupled Visual-Acoustic Fusion [J]. | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS , 2024 , 71 (10) : 12581-12591 . |
| MLA | Huang, Yupei et al. "Self-Localization of a Biomimetic Robotic Shark Using Tightly Coupled Visual-Acoustic Fusion" . | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 71 . 10 (2024) : 12581-12591 . |
| APA | Huang, Yupei , Li, Peng , Yan, Shuaizheng , Tan, Min , Yu, Junzhi , Wu, Zhengxing . Self-Localization of a Biomimetic Robotic Shark Using Tightly Coupled Visual-Acoustic Fusion . | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS , 2024 , 71 (10) , 12581-12591 . |
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Abstract ：
The oceans process abundant resources necessary for human production and livelihood, yet the complex and variable marine environment has continued to limit human capability in detecting and utilizing these resources. Inspired by the excellent mobility of marine life, biomimetic robotic fish have emerged as a new type of autonomous underwater vehicle over the past three decades. In early reviews of robotic fish, researchers classified and discussed based on the fish species and their morphologies. The challenging problems and technological prospects of robotic fish are not revealed thoroughly due to countless species. To provide a comprehensive overview of the latest research advancements, we make a classification focusing on the integrated mechatronic designs of robotic fish. Specifically, eight hot topics concerning the propulsion mechanisms and structural designs of robotic fish have been broadly defined from literature screened with PRISMA process over the past decade, with representative seminal works in each topic being analyzed. Furthermore, this review also introduces the latest advances in underwater perception and autonomous technologies for biomimetic robotic fish, and provides an outlook on their future development. It is expected that by summarizing the latest achievements, researchers can be inspired with novel mechatronic designs to further promote the practicality research of robotic fish.
Keyword ：
Biomimetic robotic fish Biomimetic robotic fish Biomimetics Biomimetics Mechatronics Mechatronics Pneumatic systems Pneumatic systems Propulsion Propulsion Reviews Reviews robotic autonomy robotic autonomy Robots Robots Robot sensing systems Robot sensing systems Sensors Sensors Service robots Service robots Sports Sports system development system development underwater perception underwater perception
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| GB/T 7714 | Yan, Shuaizheng , Wu, Zhengxing , Wang, Jian et al. Recent Advances in Design, Sensing, and Autonomy of Biomimetic Robotic Fish: A Review [J]. | IEEE-ASME TRANSACTIONS ON MECHATRONICS , 2024 . |
| MLA | Yan, Shuaizheng et al. "Recent Advances in Design, Sensing, and Autonomy of Biomimetic Robotic Fish: A Review" . | IEEE-ASME TRANSACTIONS ON MECHATRONICS (2024) . |
| APA | Yan, Shuaizheng , Wu, Zhengxing , Wang, Jian , Feng, Yukai , Yu, Lianyi , Yu, Junzhi et al. Recent Advances in Design, Sensing, and Autonomy of Biomimetic Robotic Fish: A Review . | IEEE-ASME TRANSACTIONS ON MECHATRONICS , 2024 . |
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Robust vision restoration of underwater images remains a challenge. Owing to the lack of well-matched underwater and in-air images, unsupervised methods based on the cyclic generative adversarial framework have been widely investigated in recent years. However, when using an end-to-end unsupervised approach with only unpaired image data, mode collapse could occur, and the color correction of the restored images is usually poor. In this paper, we propose a data- and physics-driven unsupervised architecture to perform underwater image restoration from unpaired underwater and in-air images. For effective color correction and quality enhancement, an underwater image degeneration model must be explicitly constructed based on the optically unambiguous physics law. Thus, we employ the Jaffe-McGlamery degeneration theory to design a generator and use neural networks to model the process of underwater visual degeneration. Furthermore, we impose physical constraints on the scene depth and degeneration factors for backscattering estimation to avoid the vanishing gradient problem during the training of the hybrid physical-neural model. Experimental results show that the proposed method can be used to perform high-quality restoration of unconstrained underwater images without supervision. On multiple benchmarks, the proposed method outperforms several state-of-the-art supervised and unsupervised approaches. We demonstrate that our method yields encouraging results in real-world applications.
Keyword ：
style transfer style transfer Underwater image restoration Underwater image restoration unsupervised learning unsupervised learning
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| GB/T 7714 | Yan, Shuaizheng , Chen, Xingyu , Wu, Zhengxing et al. HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration [J]. | IEEE TRANSACTIONS ON IMAGE PROCESSING , 2023 , 32 : 5004-5016 . |
| MLA | Yan, Shuaizheng et al. "HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration" . | IEEE TRANSACTIONS ON IMAGE PROCESSING 32 (2023) : 5004-5016 . |
| APA | Yan, Shuaizheng , Chen, Xingyu , Wu, Zhengxing , Tan, Min , Yu, Junzhi . HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration . | IEEE TRANSACTIONS ON IMAGE PROCESSING , 2023 , 32 , 5004-5016 . |
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In nature, the hammerhead shark possesses a special rolled swimming motion to combat the effects of inborn negative buoyancy. Inspired by this natural mechanism, we developed a novel biomimetic robotic hammerhead shark to explore the distinctive rolled swimming motion mode. First, a scaled-down robotic prototype is constructed based on the morphological characteristics of the hammerhead shark. Second, the kinematics and dynamics of fish-like swimming are built, thereafter, model identification and validation are performed to improve the accuracy of the robotic model. Furthermore, the physical effects of the long dorsal fin and the rolling state on swimming performance are investigated indepth by numerically simulating the lift and drag forces over different fin surfaces and the dynamic torque of the body. Finally, extensive aquatic experiments demonstrate the remarkable improvements on locomotion performance and propulsive efficiency of the robotic hammerhead shark by the proposed rolled motion. The obtained results provide a new solution for the long voyage of high-load robotic fish system.
Keyword ：
Biomimetic locomotion Biomimetic locomotion hammerhead shark hammerhead shark robotic dynamics robotic dynamics robotic fish robotic fish
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| GB/T 7714 | Yan, Shuaizheng , Wu, Zhengxing , Wang, Jian et al. Towards Unusual Rolled Swimming Motion of a Bioinspired Robotic Hammerhead Shark Under Negative Buoyancy [J]. | IEEE-ASME TRANSACTIONS ON MECHATRONICS , 2023 , 29 (3) : 2253-2265 . |
| MLA | Yan, Shuaizheng et al. "Towards Unusual Rolled Swimming Motion of a Bioinspired Robotic Hammerhead Shark Under Negative Buoyancy" . | IEEE-ASME TRANSACTIONS ON MECHATRONICS 29 . 3 (2023) : 2253-2265 . |
| APA | Yan, Shuaizheng , Wu, Zhengxing , Wang, Jian , Li, Sijie , Tan, Min , Yu, Junzhi . Towards Unusual Rolled Swimming Motion of a Bioinspired Robotic Hammerhead Shark Under Negative Buoyancy . | IEEE-ASME TRANSACTIONS ON MECHATRONICS , 2023 , 29 (3) , 2253-2265 . |
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