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Author: Hang Yan Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 79
Book Description
In this research we develop the next generation methods for inertial navigation, which seek to estimate trajectories of natural human motions with a smartphone that equips a low-cost Inertial Measurement Unit (IMU) sensor. A robust inertial navigation method has been a dream for academic researchers and industrial engineers for its ideal properties, e.g. low- energy consumption and high flexibility. However, the double integration from accelerations to translations are extremely vulnerable to even a tiny amount of sensor biases. We utilize the recent advance in Machine Learning algorithms and develop data-driven methods for robust inertial navigation in the wild. Our key insight is that human motions consist of a few major modes, which can be leveraged to constraint the double integration. We create a large-scale high quality dataset with our novel two-device data collection protocol and train various machine learning models to capture inherent human motions. Extensive evaluations are performed and demonstrate that proposed methods are able to estimate accurate trajectories under natural motions in the wild, e.g. checking messages while walking forward, answering a phone while stepping sideward or sitting in a sofa while browsing the web with the phone.The practical implications of proposed methods are also profound. We show an example of such applications, where motion trajectories from our inertial navigation algorithms are used to automatically construct WiFi radio maps, which are essential for providing an indoor positioning service. Other applications include AR/VR, fitness and health monitoring.
Author: Hang Yan Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 79
Book Description
In this research we develop the next generation methods for inertial navigation, which seek to estimate trajectories of natural human motions with a smartphone that equips a low-cost Inertial Measurement Unit (IMU) sensor. A robust inertial navigation method has been a dream for academic researchers and industrial engineers for its ideal properties, e.g. low- energy consumption and high flexibility. However, the double integration from accelerations to translations are extremely vulnerable to even a tiny amount of sensor biases. We utilize the recent advance in Machine Learning algorithms and develop data-driven methods for robust inertial navigation in the wild. Our key insight is that human motions consist of a few major modes, which can be leveraged to constraint the double integration. We create a large-scale high quality dataset with our novel two-device data collection protocol and train various machine learning models to capture inherent human motions. Extensive evaluations are performed and demonstrate that proposed methods are able to estimate accurate trajectories under natural motions in the wild, e.g. checking messages while walking forward, answering a phone while stepping sideward or sitting in a sofa while browsing the web with the phone.The practical implications of proposed methods are also profound. We show an example of such applications, where motion trajectories from our inertial navigation algorithms are used to automatically construct WiFi radio maps, which are essential for providing an indoor positioning service. Other applications include AR/VR, fitness and health monitoring.
Author: Sachini Herath Publisher: ISBN: Category : Languages : en Pages : 43
Book Description
Data-driven inertial navigation is the task of estimating of positions and orientations of a moving subject from a sequence of Inertial Measurement Unit (IMU) sensor measurements. Inertial navigation is a quintessential technology due to low cost, low energy consumption and low operating constraints of IMU sensor. However, sensor errors have forced research on inertial navigation to be limited to highly constrained use cases.We leverage on the power of machine learning and big data to loosen such constraints and estimate natural human motion in the wild. More concretely, we define our problem as estimation of relative horizontal positions and heading direction of a moving subject using the IMU sensor measurements from his phone. This research propose 1) a new benchmark containing more than 40 hours of IMU sensor data from 100 human subjects with ground-truth 3D trajectories under natural human motions; 2) novel neural inertial navigation architectures, making significant improvements for challenging motion cases; and 3) qualitative and quantitative evaluations of the competing methods over three inertial navigation benchmarks.We share the code and data to promote further research on our project website http://ronin.cs.sfu.ca.
Author: Aboelmagd Noureldin Publisher: Springer Science & Business Media ISBN: 3642304656 Category : Technology & Engineering Languages : en Pages : 324
Book Description
Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration is an introduction to the field of Integrated Navigation Systems. It serves as an excellent reference for working engineers as well as textbook for beginners and students new to the area. The book is easy to read and understand with minimum background knowledge. The authors explain the derivations in great detail. The intermediate steps are thoroughly explained so that a beginner can easily follow the material. The book shows a step-by-step implementation of navigation algorithms and provides all the necessary details. It provides detailed illustrations for an easy comprehension. The book also demonstrates real field experiments and in-vehicle road test results with professional discussions and analysis. This work is unique in discussing the different INS/GPS integration schemes in an easy to understand and straightforward way. Those schemes include loosely vs tightly coupled, open loop vs closed loop, and many more.
Author: Hongjin Zhou Publisher: Springer Nature ISBN: 9811549729 Category : Technology & Engineering Languages : en Pages : 160
Book Description
This book focuses on gyro-free inertial navigation technology, which is used to measure not only linear motion parameters but also angular rates. Since no gyroscopes are used, the key technologies, such as initial alignment, attitude resolution, and error calibration, are very different than those used in traditional methods. Discussing each key technology in gyro-free inertial navigation system (GFINS) manufacture in a separate chapter, the book features easy-to-understand, detailed illustrations, to allow all those involved in inertial navigation to gain a better grasp of GFINS manufacture, including accelerometer setting principles; initial alignment; quaternion-based, attitude resolution algorithms; and accelerometer de-noise methods.
Author: Chong Shen Publisher: Springer Nature ISBN: 9813345160 Category : Technology & Engineering Languages : en Pages : 131
Book Description
This book introduces typical inertial devices and inertial-based integrated navigation systems, gyro noise suppression, gyro temperature drift error modeling compensation, inertial-based integrated navigation systems under discontinuous observation conditions, and inertial-based brain integrated navigation systems. Integrated navigation is the result of the development of modern navigation theory and technology. The inertial navigation system has the advantages of strong autonomy, high short-term accuracy, all-day time, all weather, and so on. And it has been applied in most integrated navigation systems. Among them, the information processing of inertial-based integrated navigation system is the core technology. Due to the effect of the device mechanism and working environment, there are errors in the output information of the inertial-based integrated navigation system, including gyroscope noise, temperature drift, and discontinuous observations, which will seriously reduce the accuracy and robustness of the system. And the book helps readers to solve these problems. The intelligent information processing technology involved is equipped with simulation verification, which can be used as a reference for undergraduate, graduate, and Ph.D. students, and also scientific researchers or engineers engaged in navigation-related specialties.
Author: Jakob M. Hansen Publisher: ISBN: Category : Science Languages : en Pages :
Book Description
This chapter is the study of state estimators for robust navigation. Navigation of vehicles is a vast field with multiple decades of research. The main aim is to estimate position, linear velocity, and attitude (PVA) under all dynamics, motions, and conditions via data fusion. The state estimation problem will be considered from two different perspectives using the same kinematic model. First, the extended Kalman filter (EKF) will be reviewed, as an example of a stochastic approach; second, a recent nonlinear observer will be considered as a deterministic case. A comparative study of strapdown inertial navigation methods for estimating PVA of aerial vehicles fusing inertial sensors with global navigation satellite system (GNSS)-based positioning will be presented. The focus will be on the loosely coupled integration methods and performance analysis to compare these methods in terms of their stability, robustness to vibrations, and disturbances in measurements.
Author: Thomas Foken Publisher: Springer Nature ISBN: 3030521710 Category : Science Languages : en Pages : 1761
Book Description
This practical handbook provides a clearly structured, concise and comprehensive account of the huge variety of atmospheric and related measurements relevant to meteorologists and for the purpose of weather forecasting and climate research, but also to the practitioner in the wider field of environmental physics and ecology. The Springer Handbook of Atmospheric Measurements is divided into six parts: The first part offers instructive descriptions of the basics of atmospheric measurements and the multitude of their influencing factors, fundamentals of quality control and standardization, as well as equations and tables of atmospheric, water, and soil quantities. The subsequent parts present classical in-situ measurements as well as remote sensing techniques from both ground-based as well as airborn or satellite-based methods. The next part focusses on complex measurements and methods that integrate different techniques to establish more holistic data. Brief discussions of measurements in soils and water, at plants, in urban and rural environments and for renewable energies demonstrate the potential of such applications. The final part provides an overview of atmospheric and ecological networks. Written by distinguished experts from academia and industry, each of the 64 chapters provides in-depth discussions of the available devices with their specifications, aspects of quality control, maintenance as well as their potential for the future. A large number of thoroughly compiled tables of physical quantities, sensors and system characteristics make this handbook a unique, universal and useful reference for the practitioner and absolutely essential for researchers, students, and technicians.
Author: Haoran Wen Publisher: Springer Nature ISBN: 3030254704 Category : Technology & Engineering Languages : en Pages : 127
Book Description
This thesis develops next-generation multi-degree-of-freedom gyroscopes and inertial measurement units (IMU) using micro-electromechanical-systems (MEMS) technology. It covers both a comprehensive study of the physics of resonator gyroscopes and novel micro/nano-fabrication solutions to key performance limits in MEMS resonator gyroscopes. Firstly, theoretical and experimental studies of physical phenomena including mode localization, nonlinear behavior, and energy dissipation provide new insights into challenges like quadrature errors and flicker noise in resonator gyroscope systems. Secondly, advanced designs and micro/nano-fabrication methods developed in this work demonstrate valuable applications to a wide range of MEMS/NEMS devices. In particular, the HARPSS+ process platform established in this thesis features a novel slanted nano-gap transducer, which enabled the first wafer-level-packaged single-chip IMU prototype with co-fabricated high-frequency resonant triaxial gyroscopes and high-bandwidth triaxial micro-gravity accelerometers. This prototype demonstrates performance amongst the highest to date, with unmatched robustness and potential for flexible substrate integration and ultra-low-power operation. This thesis shows a path toward future low-power IMU-based applications including wearable inertial sensors, health informatics, and personal inertial navigation.
Author: Hang Yan
Author: Hang Yan
Author: Sachini Herath
Author: Aboelmagd Noureldin
Author: Hongjin Zhou
Author: Chong Shen
Author: Zexi Liu
Author: Jakob M. Hansen
Author: Thomas Foken
Author: Haoran Wen
Author: