Localization of an underwater robot for remote data collection
Underwater localization is a fundamental requirement in underwater robotics. Accurate and drift free pose estimates are required for navigation and operation in challenging underwater environments. Inaccuracies and errors in localization would result in the degradation of the data collected. In this...
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Nanyang Technological University
2020
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sg-ntu-dr.10356-1454452023-07-07T16:59:25Z Localization of an underwater robot for remote data collection Wee, Mervyn Wei Jie Hu, Guoqiang School of Electrical and Electronic Engineering GQHu@ntu.edu.sg Engineering::Electrical and electronic engineering Underwater localization is a fundamental requirement in underwater robotics. Accurate and drift free pose estimates are required for navigation and operation in challenging underwater environments. Inaccuracies and errors in localization would result in the degradation of the data collected. In this work, a low-cost localization method using the inertial measurement unit (IMU) and an Extended Kalman Filter (EKF) algorithm is proposed for miniature underwater robots. The underwater robot used in this work is the open source Remotely Operated Vehicle (openROV). The proposed method uses data from the IMU of the openROV robot and inputs it into the EKF algorithm to create a map which shows the position and path of the openROV robot. The fundamental algorithmic principles behind the localization technique is described, and the algorithm is tested using a dataset and a simulation. Simulation results show that the designed algorithm can achieve accurate pose estimation. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-12-22T01:54:50Z 2020-12-22T01:54:50Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/145445 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Wee, Mervyn Wei Jie Localization of an underwater robot for remote data collection |
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Underwater localization is a fundamental requirement in underwater robotics. Accurate and drift free pose estimates are required for navigation and operation in challenging underwater environments. Inaccuracies and errors in localization would result in the degradation of the data collected. In this work, a low-cost localization method using the inertial measurement unit (IMU) and an Extended Kalman Filter (EKF) algorithm is proposed for miniature underwater robots. The underwater robot used in this work is the open source Remotely Operated Vehicle (openROV). The proposed method uses data from the IMU of the openROV robot and inputs it into the EKF algorithm to create a map which shows the position and path of the openROV robot. The fundamental algorithmic principles behind the localization technique is described, and the algorithm is tested using a dataset and a simulation. Simulation results show that the designed algorithm can achieve accurate pose estimation. |
author2 |
Hu, Guoqiang |
author_facet |
Hu, Guoqiang Wee, Mervyn Wei Jie |
format |
Final Year Project |
author |
Wee, Mervyn Wei Jie |
author_sort |
Wee, Mervyn Wei Jie |
title |
Localization of an underwater robot for remote data collection |
title_short |
Localization of an underwater robot for remote data collection |
title_full |
Localization of an underwater robot for remote data collection |
title_fullStr |
Localization of an underwater robot for remote data collection |
title_full_unstemmed |
Localization of an underwater robot for remote data collection |
title_sort |
localization of an underwater robot for remote data collection |
publisher |
Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/145445 |
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1772827402226892800 |