Tightly Coupled Monocular-Inertial-Pressure Sensor Fusion for Underwater Localization of a Biomimetic Robotic Manta
Shaoxuan Ma, Jian Wang, Yupei Huang, Yan Meng, Min Tan, Junzhi Yu, Zhengxing Wu
- 发表年份
- 2024
- 引用次数
- 7
摘要
This article proposes a novel tightly coupled monocular-inertial-pressure (IP) sensor fusion method for underwater localization of a biomimetic robotic manta. Based on the ORB-SLAM3 monocular visual-inertial odometry (VIO) model, the depth measurement from a pressure sensor is incorporated, and a novel approach is provided to associate low-frequency pressure measurements with high-frequency frames by utilizing only the relative depth between two adjacent keyframes as measurements. To address the challenge of scale estimation uncertainty in monocular odometry systems, a two-step monocular initialization strategy is proposed, involving an initial estimate based on visual-pressure (VP) measurements and a subsequent tightly coupled inertial pressure depth residual construction, which results in a significantly improved scale estimate compared to conventional monocular inertial odometry systems. After the successful initialization of the monocular system, a novel visual-inertial-pressure (VIP) joint optimization method is proposed to enhance the localization and attitude estimation accuracy. Extensive experiments are carried out on both open-source datasets and real-world underwater datasets collected by a biomimetic robotic manta. The experimental results demonstrate the effectiveness of the proposed method in significantly improving both the position and attitude estimation of the biomimetic robotic manta. This research provides valuable insights for enhancing the underwater localization capability of biomimetic robotic systems.
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