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Article Autonomous Navigation for Autonomous Underwater Vehicles Based on Information Filters and Active Sensing
, 2011
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Opportunistic Localization of Underwater Robots using Drifters and Boats
"... Abstract — The paper characterizes the performance of Autonomous Underwater Vehicle (AUV) localization when the AUV moves in environments where floating drifters or surface vessels are present and can be used for relative localization. In particular, we study how localization performance is affected ..."
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Abstract — The paper characterizes the performance of Autonomous Underwater Vehicle (AUV) localization when the AUV moves in environments where floating drifters or surface vessels are present and can be used for relative localization. In particular, we study how localization performance is affected by parameters e.g. surface object density, their visibility range and their motion. We present a discrete-time nonlinear model for an AUV equipped with onboard sensors and relative positioning information from surface objects (e.g., ranging and bearing) and derive the associated relative Posterior Cramér-Rao Lower Bound. We introduce a probabilistic motion model for the AUV, based on a random direction mobility model, to analyze the expected performance of the localization algorithm in terms of hitting time between the AUV and the surface objects. Finally, an extensive simulation analysis is performed using a discrete time Extended Kalman Filter with Maximum-Likelihood Data Association. As a proof of concept, an AUV equipped with an upward looking sonar is shown to detect a surface vessel and improve its localization estimate. I.
Article Inertial Sensor Self-Calibration in a Visually-Aided Navigation Approach for a Micro-AUV
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Article Observability Analysis of DVL/PS Aided INS for a Maneuvering AUV
, 2015
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Abstract—In an Unmanned Underwater Vehicle (UUV), the
"... craft's orientation, velocity, and gravitational forces are the important measurements to make sure the UUV’s navigation system can be fully operated. Most of the current UUV system uses pressure sensor to control the navigation of the craft. But the pressure sensor is not suitable to use in ge ..."
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craft's orientation, velocity, and gravitational forces are the important measurements to make sure the UUV’s navigation system can be fully operated. Most of the current UUV system uses pressure sensor to control the navigation of the craft. But the pressure sensor is not suitable to use in getting UUV’s navigation data or information. Without the information on UUV’s navigation, there are difficult to monitor the movement of UUV. This project introduces a methodology to analyze the position, velocity vector and the rotation of UUV, using a combination of accelerometer and gyroscope. This sensing unit is a combination of Accelerometer ADXL-345 sensor and Gyroscope ITG-3200 sensor called as an Inertial Measurement Unit (IMU). The measurement unit will be programmed by an Atmel microcontroller (Arduino UNO) to get the important data of the UUV’s navigation system. The real-time data of sensing unit communicated with Serial Chart and Processing software to get output graph and real-time 3D animation of UUV. From this project outcome, the movement of UUV is monitored in processing software. Hence, the navigation system of a UUV such as auto depth control, left-right movement and obstacle avoidance purpose can be improved. Index Terms—unmanned underwater vehicle, navigation system, auto depth control, inertial measurement unit I.
Approval of the thesis: MEMS SENSOR BASED UNDERWATER AHRS (ATTITUDE AND HEADING REFERENCE SYSTEM) AIDED BY COMPASS AND PRESSURE SENSOR
, 2012
"... I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. ..."
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I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work.
The undersigned hereby certify that they have read and recommend to the Faculty of Graduate Studies for acceptance a thesis entitled “AN IMPROVED PATH INTEGRATION MECHANISM USING NEURAL FIELDS WHICH IMPLEMENT A BIOLOGICALLY PLAUSIBLE ANALOGUE TO A KALMAN
, 2013
"... Permission is herewith granted to Dalhousie University to circulate and to have copied for non-commercial purposes, at its discretion, the above title upon the request of individuals or institutions. I understand that my thesis will be electronically available to the public. The author reserves othe ..."
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Permission is herewith granted to Dalhousie University to circulate and to have copied for non-commercial purposes, at its discretion, the above title upon the request of individuals or institutions. I understand that my thesis will be electronically available to the public. The author reserves other publication rights, and neither the thesis nor extensive extracts from it may be printed or otherwise reproduced without the author’s written permission. The author attests that permission has been obtained for the use of any copyrighted material appearing in the thesis (other than brief excerpts requiring only proper acknowledgement in scholarly writing), and that all such use is clearly acknowledged.
