Features
- Resembles a set of new theoretical algorithms (Kalman Filters, observers, complementary filters, etc.) on multisensor fusion in attitude estimation to help the reader to explore recent advancements.
- Case studies included on: Movea, STMicroelectronics, Xsens Technologies, Delta Drone, CTS Corporation, Texas Instruments, and LG and Samsung.
- Helps the reader to understand the basics of data fusion in attitude estimation, mathematical representations of attitude and main used sensors.
- Allows the reader to discover a set of new applications where multisensor attitude estimation find a strong interest.
- Provides the reader with a generic and comprehensive view of contemporary data fusion methodologies for attitude estimation, as well as the most recent researches and novel advances on multisensor attitude estimation task exploring the design of algorithms and architectures, benefits, and challenging aspects, as well as potential broad array of disciplines including navigation, robotics, biomedicine, motion analysis.
Summary
There has been an increasing interest in multi-disciplinary research on multisensor attitude estimation technology driven by its versatility and diverse areas of application, such as sensor networks, robotics, navigation, video, biomedicine, etc. Attitude estimation consists of the determination of rigid bodies’ orientation in 3D space. This research area is a multilevel, multifaceted process handling the automatic association, correlation, estimation, and combination of data and information from several sources. Data fusion for attitude estimation is motivated by several issues and problems, such as data imperfection, data multi-modality, data dimensionality, processing framework, etc. While many of these problems have been identified and heavily investigated, no single data fusion algorithm is capable of addressing all the aforementioned challenges. The variety of methods in the literature focus on a subset of these issues to solve, which would be determined based on the application in hand. Historically, the problem of attitude estimation has been introduced by Grace Wahba in 1965 within the estimate of satellite attitude and aerospace applications.
This book intends to provide the reader with both a generic and comprehensive view of contemporary data fusion methodologies for attitude estimation, as well as the most recent researches and novel advances on multisensor attitude estimation task. It explores the design of algorithms and architectures, benefits, and challenging aspects, as well as a broad array of disciplines, including: navigation, robotics, biomedicine, motion analysis, etc. A number of issues that make data fusion for attitude estimation a challenging task, and which will be discussed through the different chapters of the book, are related to: 1) The nature of sensors and information sources (accelerometer, gyroscope, magnetometer, GPS, inclinometer, etc.); 2) The computational ability at the sensors; 3) The theoretical developments and convergence proofs; 4) The system architecture, computational resources, fusion level.
Table of Contents
Contents
Preface
Editors
Contributors
Historical Note
Section I Preliminaries on Attitude Representations and Rotations
Chapter 1 What Are Quaternions and Why Haven’t I Heard of Them?
Herb Klitzner
Chapter 2 Rotation in 3D Space
Ayman F. Habib
Chapter 3 Attitude Parametrization, Kinematics, and Dynamics
Lotfi Benziane, Abdelaziz Benallegue, and Yacine Chitour
Section II Multisensor Filtering for Attitude Estimation: Theories and Applications
Chapter 4 Stable Estimation of Rigid Body Motion Based on the Lagrange–d’Alembert
Principle
Amit K. Sanyal and Maziar Izadi
Chapter 5 The Additive and Multiplicative Approaches to Quaternion Kalman Filtering
Renato Zanetti and Robert H. Bishop
Chapter 6 Spacecraft Attitude Determination
Yaguang Yang
Chapter 7 How to Deal with the External Acceleration When Estimating the
Attitude Using Inertial Measurement Units: A Linear Kalman-Based
Filtering Approach
Gabriele Ligorio and Angelo Maria Sabatini
Chapter 8 From Attitude Estimation to Pose Estimation Using Dual Quaternions
Nuno Filipe, Michail Kontitsis, and Panagiotis Tsiotras
Chapter 9 Distributed Estimation for Spatial Rigid Motion Based on Dual Quaternions
Yue Zu and Ran Dai
Chapter 10 A Quaternion Orientation from Earth Field Observations Using the Algebraic
Quaternion Algorithm: Analysis and Applications in Fusion Algorithms
Roberto G. Valenti, Ivan Dryanovski, and Jizhong Xiao
Chapter 11 Recent Nonlinear Attitude Estimation Algorithms
Seid H. Pourtakdoust and M. Kiani
Chapter 12 Low Complexity Sensor Fusion Solution for Accurate Estimation of Gravity
and Linear Acceleration
Ramasamy Kannan
Chapter 13 Deterministic Attitude Estimation
Abraham P. Vinod and Arun D. Mahindrakar
Chapter 14 Attitude Estimations with Intermittent Observations
Naeem Khan
Chapter 15 Estimation of Attitude from a Single-Direction Sensor
Lionel Magnis and Nicolas Petit
Chapter 16 Cooperative Attitude Estimation Based on Remote-Access Observations
Chao Gao, Guorong Zhao, and Jianhua Lu
Chapter 17 Nonlinear Observer for Attitude, Position, and Velocity: Theory
and Experiments
Håvard Fjær Grip, Thor I. Fossen, Tor A. Johansen, and Ali Saberi
Chapter 18 Spacecraft Attitude Estimation Using Sparse Grid Quadrature Filtering
Yang Cheng
Chapter 19 Attitude Estimation for Small, Low-Cost UAVs: A Tutorial Approach
Gabriel Hugh Elkaim and Demoz Gebre-Egziabher
Chapter 20 3D Orientation Estimation Using Wearable MEMS Inertial/Magnetic Sensors
Shaghayegh Zihajehzadeh, Jung Keun Lee, Reynald Hoskinson,
and Edward J. Park
Chapter 21 Adaptive Data Fusion of Multiple Sensors for Vehicle Pose Estimation
Farhad Aghili and Alessio Salerno
Chapter 22 Optimal Invariant Observers Theory for Nonlinear State Estimation
Cédric Seren, Jean-Philippe Condomines, and Gautier Hattenberger
Chapter 23 Design and Implementation of Low-Cost Attitude Heading References Systems
for Micro Aerial Vehicles
José Fermi Guerrero-Castellanos, Germán Ardul Munoz-Hernandez,
Carlos A. Graciós-Marín, and Bernardino Benito Salmeron-Quiroz
Chapter 24 Small Satellite Attitude Determination
Demoz Gebre-Egziabher, Chuck S. Hisamoto, and Suneel I. Sheikh
Chapter 25 A Hybrid Data Fusion Approach for Robust Attitude Estimation
Pedro Santana, Renato Vilela Lopes, Geovany Borges, and Brian Williams
Chapter 26 Integration of Single-Frame and Filtering Methods for Nanosatellite Attitude
Estimation
Halil Ersin Soken, Demet Cilden, and Chingiz Hajiyev
Chapter 27 Ego-Motion Tracking in Dynamic Environments Using Wearable
Visual-Inertial Sensors
Jindong Tan, Hongsheng He, Ya Tian, Yong Guan, and William R. Hamel
Chapter 28 Attitude Estimation for a Small-Scale Flybarless Helicopter
Mohammad K. S. Al-Sharman
Chapter 29 A Comparison of Multisensor Attitude Estimation Algorithms
Andrea Cirillo, Pasquale Cirillo, Giuseppe De Maria, Ciro Natale,
and Salvatore Pirozzi
Chapter 30 Low-Cost and Accurate Reconstruction of Postures via IMU
Gaspare Santaera, Emanule Luberto, and Marco Gabiccini
Chapter 31 Attitude Estimation of a UAV Using Optical Flow
Lianhua Zhang, Zongying Shi, and Yisheng Zhong
Index