Mems Imu Navigation With Model Based Dead Reckoning And One Way Travel Time Acoustic Range Measurements For Autonomous Underwater Vehicles
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MEMS IMU Navigation with Model Based Dead-reckoning and One-way-travel-time Acoustic Range Measurements for Autonomous Underwater Vehicles
Recent advances in acoustic navigation methodologies are enabling the way for AUVs to extend their submerged mission time and maintain a bounded XY position error. Additionally, advances in inertial sensor technology have drastically lowered the size, power consumption, and cost of these sensors. Nonetheless, these sensors are still noisy and accrue error over time. This thesis builds on the research and recent developments in single beacon one-waytravel- time (OWTT) acoustic navigation and investigates the degree of bounding position error for small AUVs with a minimal navigation strap-down sensor suite, relying mostly on a consumer grade microelectromechanical system (MEMS) inertial measurement unit (IMU) and a vehicle's dynamic model velocity. An implementation of an Extended Kalman Filter (EKF) that includes IMU bias estimation and coupled with a range filter, is obtained in the field on two OceanServer Technology, Inc. Iver2 AUVs and one Bluefin Robotics SandShark AUV. Results from these field trials on Ashumet Pond of Falmouth, Massachusetts, the Charles River of Cambridge, Massachusetts, and Monterey Bay near Santa Cruz, California show a navigation solution accuracy comparable to current standard navigation techniques.
Offshore Robotics
This journal-like book series includes edited volumes to rapidly report and spread the latest technological results, new scientific discovery and valuable applied researches in the fields concerning offshore robotics as well as promote international academic exchange. We aim to make it one of the premier comprehensive academic publications of world offshore vehicle and robotics community. The audience of the series will include the scholars, researchers, engineers and students who are interested in fields of autonomous marine vehicles and robotics, including autonomous surface vehicles, autonomous underwater vehicles, remote operation vehicles, marine bionics, marine vehicle modeling, guidance, navigation, control and cooperation and so on.
MEMS IMU Inertial Measurement Unit One-way-travel-time Inertial Measurement Unit Autonomous Underwater Vehicles
Recent advances in acoustic navigation methodologies are enabling the way for AUVs to extend their submerged mission time and maintain a bounded XY position error. Additionally, advances in inertial sensor technology have drastically lowered the size, power consumption, and cost of these sensors. Nonetheless, these sensors are still noisy and accrue error over time. This thesis builds on the research and recent developments in single beacon one-way-travel- time (OWTT) acoustic navigation and investigates the degree of bounding position error for small AUVs with a minimal navigation strap-down sensor suite, relying mostly on a consumer grade microelectromechanical system (MEMS) inertial measurement unit (IMU) and a vehicle's dynamic model velocity. An implementation of an Extended Kalman Filter (EKF) that includes IMU bias estimation and coupled with a range filter, is obtained in the field on two OceanServer Technology, Inc. Iver2 AUVs and one Bluefin Robotics SandShark [mu]AUV. Results from these field trials on Ashumet Pond of Falmouth, Massachusetts, the Charles River of Cambridge, Massachusetts, and Monterey Bay near Santa Cruz, California show a navigation solution accuracy comparable to current standard navigation techniques.