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Strapdown inertial navigation technology

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TLDR
In this paper, the physical principles of inertial navigation, the associated growth of errors and their compensation, and their application in a broad range of applications are discussed, drawing current technological developments and providing an indication of potential future trends.
Abstract
Inertial navigation is widely used for the guidance of aircraft, missiles ships and land vehicles, as well as in a number of novel applications such as surveying underground pipelines in drilling operations. This book discusses the physical principles of inertial navigation, the associated growth of errors and their compensation. It draws current technological developments, provides an indication of potential future trends and covers a broad range of applications. New chapters on MEMS (microelectromechanical systems) technology and inertial system applications are included.

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Proceedings ArticleDOI

Estimation of IMU and MARG orientation using a gradient descent algorithm

TL;DR: This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications, applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity sensor arrays that also include tri- axis magnetometers.
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Handbook of Marine Craft Hydrodynamics and Motion Control: Fossen/Handbook of Marine Craft Hydrodynamics and Motion Control

TL;DR: In this article, the authors present a survey of the latest tools for analysis and design of advanced guidance, navigation and control systems and present new material on underwater vehicles and surface vessels.

An introduction to inertial navigation

TL;DR: This work introduces inertial navigation, focusing on strapdown systems based on MEMS devices, and concludes that whilst MEMS IMU technology is rapidly improving, it is not yet possible to build a MEMS based INS which gives sub-meter position accuracy for more than one minute of operation.
Proceedings ArticleDOI

A flexible and scalable SLAM system with full 3D motion estimation

TL;DR: A system for fast online learning of occupancy grid maps requiring low computational resources is presented that combines a robust scan matching approach using a LIDAR system with a 3D attitude estimation system based on inertial sensing to achieve reliable localization and mapping capabilities in a variety of challenging environments.
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