Dynamic Modeling and Monocular Image-Based Pose Tracking for an AUV in Power Turn
| Autor: | YI-LUN CHIU, 邱奕倫 |
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| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 This work investigates a development of a highly maneuverable AUV that has a high maneuverability to perform power turns. Two fundamental problems are addressed in this paper, which are the dynamic modelling of this AUV and pose tracking method by vision system. The vehicle has a rotatable stern propeller for horizontal turning at high speed, two paddles for the braking and ascending/descending. A motion model is firstly derived to predict the motion of the body. The dynamic equations are derived based on the Lagrange principle. Added mass coefficients are estimated using the equivalent ellipsoid method. A tank environment with an overhead camera system is utilized to record marker positions on the vehicle body. The iterative Lucas-Kanade method is applied for the tracking of the AUV. To track the vehicle’s position and orientation for autonomous navigation, we introduce a monocular image-based approach. Our approach is developed for an underwater environment which with fewer features and low visibility. We present a novel real-time optimizing estimation method which bases on the forward-looking camera for observing. The sequence Monte-Carlo method is used for estimating the pose of body. In particular, the augmented reality technique is involved to the measuring process, this measuring method provide the reliable estimation for importance factor. Our approach was verified by long time cruise in a water tank. Experiment data indicates that it is robust and efficient for the real-time position tracking of the robot. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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