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Indoor Navigation Strategies for Aerial Autonomous Systems
1st Edition - November 10, 2016
Authors: Pedro Castillo-Garcia, Laura Elena Munoz Hernandez, Pedro Garcia Gil
Paperback ISBN:9780128051894
9 7 8 - 0 - 1 2 - 8 0 5 1 8 9 - 4
eBook ISBN:9780128053393
9 7 8 - 0 - 1 2 - 8 0 5 3 3 9 - 3
Indoor Navigation Strategies for Aerial Autonomous Systems presents the necessary and sufficient theoretical basis for those interested in working in unmanned aerial vehicles,… Read more
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Indoor Navigation Strategies for Aerial Autonomous Systems presents the necessary and sufficient theoretical basis for those interested in working in unmanned aerial vehicles, providing three different approaches to mathematically represent the dynamics of an aerial vehicle.
The book contains detailed information on fusion inertial measurements for orientation stabilization and its validation in flight tests, also proposing substantial theoretical and practical validation for improving the dropped or noised signals. In addition, the book contains different strategies to control and navigate aerial systems.
The comprehensive information will be of interest to both researchers and practitioners working in automatic control, mechatronics, robotics, and UAVs, helping them improve research and motivating them to build a test-bed for future projects.
Provides substantial information on nonlinear control approaches and their validation in flight tests
Details in observer-delay schemes that can be applied in real-time
Teaches how an IMU is built and how they can improve the performance of their system when applying observers or predictors
Improves prototypes with tactics for proposed nonlinear schemes
Academics and researches in automatic control, mechatronics, robotics, Unmanned Aerial Vehicles (UAVs)
About the Authors
Preface
Acknowledgments
Part I: Background
Background
Chapter 1: State-of-the-Art
Abstract
1.1. Mathematical Representation of the Vehicle Dynamics
1.2. Attitude Estimation Using Inertial Sensors
1.3. Delay Systems & Predictors
1.4. Data Fusion for UAV Localization
1.5. Control & Navigation Algorithms
1.6. Trajectory Generation & Tracking
1.7. Obstacle Avoidance
1.8. Teleoperation
References
Chapter 2: Modeling Approaches
Abstract
2.1. Force and Moment in a Rotor
2.2. Euler–Lagrange Approach
2.3. Newton–Euler Approach
2.4. Quaternion Approach
2.5. Discussion
References
Part II: Improving Sensor Signals for Control Purposes
Improving Sensor Signals for Control Purposes
Chapter 3: Inertial Sensors Data Fusion for Orientation Estimation
Abstract
3.1. Attitude Representation
3.2. Sensor Characterization
3.3. Attitude Estimation Algorithms
3.4. A Computationally-Efficient Kalman Filter
3.5. Discussion
References
Chapter 4: Delay Signals & Predictors
Abstract
4.1. Observer–Predictor Algorithm for Compensation of Measurement Delays
4.2. State Predictor–Control Scheme
4.3. Discussion
References
Chapter 5: Data Fusion for UAV Localization
Abstract
5.1. Sensor Data Fusion
5.2. Prototype and Numerical Implementation
5.3. Flight Tests and Experimental Results
5.4. OptiTrack Measurements vs EKF Estimation
5.5. Rotational Optical Flow Compensation
5.6. Discussion
References
Part III: Navigation Schemes & Control Strategies
Navigation Schemes & Control Strategies
Chapter 6: Nonlinear Control Algorithms with Integral Action
Abstract
6.1. From PD to PID Controllers
6.2. Saturated Controllers with Integral Component
6.3. Integral and Adaptive Backstepping Control – IAB
6.4. Discussion
References
Chapter 7: Sliding Mode Control
Abstract
7.1. From the Nonlinear Attitude Representation to Linear MIMO Expression
7.2. Nonlinear Optimal Controller with Integral Sliding Mode Design
7.3. Numerical Validation
7.4. Real-Time Validation
7.5. Discussion
References
Chapter 8: Robust Simple Controllers
Abstract
8.1. Nonlinear Robust Algorithms Based on Saturation Functions
8.2. Robust Control Based on an Uncertainty Estimator
9.3. UAV Routing Problem for Inspection-Like Missions
9.4. Trajectory Tracking Problem
9.5. Simulation Results
9.6. Discussion
References
Chapter 10: Obstacle Avoidance
Abstract
10.1. Artificial Potential Field Method
10.2. Obstacle Avoidance Algorithm
10.3. Limit-Cycle Obstacle Avoidance
10.4. Discussion
References
Chapter 11: Haptic Teleoperation
Abstract
11.1. Experimental Setup
11.2. Collision Avoidance
11.3. Haptic Teleoperation
11.4. Real-Time Experiments
11.5. Discussion
References
Index
No. of pages: 300
Language: English
Published: November 10, 2016
Imprint: Butterworth-Heinemann
Paperback ISBN: 9780128051894
eBook ISBN: 9780128053393
PC
Pedro Castillo-Garcia
He received the best Ph.D. thesis of Automatic Control award from club EEA, (France) in 2005. His research topics cover: real-time control applications, non-linear dynamics and control, aerospace vehicles, vision and underactuated mechanical systems.
Affiliations and expertise
Researcher, French National Research Foundation (CNRS), Laboratory Heudiasyc,University of Technology of Compiegne, France
LM
Laura Elena Munoz Hernandez
She obtained her B.S degree in Electronics and Telecommunications Engineering in 2005 and her M.Sc degree in Automation and Control in 2007 from the Hidalgo State University, Mexico. In 2009 she obtained her Ph.D. degree in Automatic Control from the University of Technology of Compiègne, France.
Affiliations and expertise
Engineer in research and development in a Start-Up in France
PG
Pedro Garcia Gil
He has been visiting researcher at the Lund Institute of Technology, Lund, Sweden (in 2006), Université de Technologie de Compiegne, Compiegne, France (in 2007), University of Florianopolis, Brazil (in 2010), and at the University of Sheffield (UK) (in 2014). He has co-authored more than 15 papers in middle or top impact journals. His research interests are within the broad area of time delay systems, embedded control systems and control of autonomous vehicles.
Affiliations and expertise
Assistant Professor of Automatic Control, Technical University of Valencia, Spain