Sequential Monte Carlo Localization for Autonomous Underwater Vehicle by Using Monocular Vision
Date Issued
2015
Date
2015
Author(s)
Chen, Han-Ying
Abstract
Localization and navigation are two crucial abilities for autonomous underwater vehicle (AUV) to track target and avoid obstacles in an underwater environment. In this work, an underwater environment was arranged for an AUV to accurately identify the relative distance and angular relationship between the AUV and the target; furthermore, the AUV was commanded to track trajectories using onboard vision. Sequential Monte Carlo localization algorithm is applied for the localization algorithm. The AUV acquires environmental and state information using a monocular camera, an electronic compass, and accelerometers for localization and navigation. While establishing the relationship between observed target and monocular camera by using image color space and edge detection to identify position, width and orientation in the reference coordinate of the target. The Sequential Monte Carlo localization in known underwater environment is then constructed by integrating vehicle motion model. The tank site was used as an example to verify the feasibility of the proposed localization and navigation method.
Subjects
autonomous underwater vehicle, underwater navigation, monocular vision, Sequential Monte Carlo Localization algorithm
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-104-R01525075-1.pdf
Size
23.54 KB
Format
Adobe PDF
Checksum
(MD5):e98135af7499b234bbd4e31eab7b94ca