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Indoor navigation strategies for aer...

Castillo, Pedro, (1975-)

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Indoor navigation strategies for aerial autonomous systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Indoor navigation strategies for aerial autonomous systems/ Pedro Castillo García, Laura Elena Munoz Hernandez, Pedro García Gil.
Author:	Castillo, Pedro,
other author:	Muñoz Hernández, Laura Elena,
Published:	Oxford, United Kingdom :Butterworth-Heinemann/Elsevier, : 2017.,
Description:	1 online resource (xiii, 286 p.)
[NT 15003449]:	Front Cover; Indoor Navigation Strategies for Aerial Autonomous Systems; Copyright; Contents; About the Authors; Preface; Acknowledgments; Part 1 Background; 1 State-of-the-Art; 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; 2 Modeling Approaches; 2.1 Force and Moment in a Rotor; 2.2 Euler-Lagrange Approach; 2.3 Newton-Euler Approach.
[NT 15003449]:	2.4 Quaternion Approach2.5 Discussion; References; Part 2 Improving Sensor Signals for Control Purposes; 3 Inertial Sensors Data Fusion for Orientation Estimation; 3.1 Attitude Representation; 3.2 Sensor Characterization; 3.3 Attitude Estimation Algorithms; 3.4 A Computationally-Efficient Kalman Filter; 3.5 Discussion; References; 4 Delay Signals & Predictors; 4.1 Observer-Predictor Algorithm for Compensation of Measurement Delays; 4.2 State Predictor-Control Scheme; 4.3 Discussion; References; 5 Data Fusion for UAV Localization; 5.1 Sensor Data Fusion.
[NT 15003449]:	5.2 Prototype and Numerical Implementation5.3 Flight Tests and Experimental Results; 5.4 OptiTrack Measurements vs EKF Estimation; 5.5 Rotational Optical Flow Compensation; 5.6 Discussion; References; Part 3 Navigation Schemes & Control Strategies; 6 Nonlinear Control Algorithms with Integral Action; 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; 7 Sliding Mode Control; 7.1 From the Nonlinear Attitude Representation to Linear MIMO Expression.
[NT 15003449]:	7.2 Nonlinear Optimal Controller with Integral Sliding Mode Design7.3 Numerical Validation; 7.4 Real-Time Validation; 7.5 Discussion; References; 8 Robust Simple Controllers; 8.1 Nonlinear Robust Algorithms Based on Saturation Functions; 8.2 Robust Control Based on an Uncertainty Estimator; 8.3 Discussion; References; 9 Trajectory Generation, Planning & Tracking; 9.1 Quadrotor Mathematical Description; 9.2 Time-Optimal Trajectory Generation; 9.3 UAV Routing Problem for Inspection-Like Missions; 9.4 Trajectory Tracking Problem; 9.5 Simulation Results; 9.6 Discussion; References.
[NT 15003449]:	10 Obstacle Avoidance10.1 Artificial Potential Field Method; 10.2 Obstacle Avoidance Algorithm; 10.3 Limit-Cycle Obstacle Avoidance; 10.4 Discussion; References; 11 Haptic Teleoperation; 11.1 Experimental Setup; 11.2 Collision Avoidance; 11.3 Haptic Teleoperation; 11.4 Real-Time Experiments; 11.5 Discussion; References; Index; Back Cover.
Subject:	Drone aircraft - Control systems. -
Online resource:	https://www.sciencedirect.com/science/book/9780128051894
ISBN:	9780128053393 (electronic bk.)

Indoor navigation strategies for aerial autonomous systems
Castillo, Pedro,1975-

Indoor navigation strategies for aerial autonomous systems[electronic resource] /Pedro Castillo García, Laura Elena Munoz Hernandez, Pedro García Gil. - Oxford, United Kingdom :Butterworth-Heinemann/Elsevier,2017. - 1 online resource (xiii, 286 p.)

Includes bibliographical references and index.

Front Cover; Indoor Navigation Strategies for Aerial Autonomous Systems; Copyright; Contents; About the Authors; Preface; Acknowledgments; Part 1 Background; 1 State-of-the-Art; 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; 2 Modeling Approaches; 2.1 Force and Moment in a Rotor; 2.2 Euler-Lagrange Approach; 2.3 Newton-Euler Approach.

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 inautomatic control, mechatronics, robotics, and UAVs, helping them improve research and motivating them to build a test-bed for future projects.

ISBN: 9780128053393 (electronic bk.)

LCCN: 2017286174Subjects--Topical Terms:

896751
Drone aircraft
--Control systems.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: TL589.4 / .C37 2017eb

Dewey Class. No.: 629.132/6

Indoor navigation strategies for aerial autonomous systems
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245 1 0 $a Indoor navigation strategies for aerial autonomous systems $h [electronic resource] / $c Pedro Castillo García, Laura Elena Munoz Hernandez, Pedro García Gil.
260 $a Oxford, United Kingdom : $b Butterworth-Heinemann/Elsevier, $c 2017.
300 $a 1 online resource (xiii, 286 p.)
504 $a Includes bibliographical references and index.
505 0 $a Front Cover; Indoor Navigation Strategies for Aerial Autonomous Systems; Copyright; Contents; About the Authors; Preface; Acknowledgments; Part 1 Background; 1 State-of-the-Art; 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; 2 Modeling Approaches; 2.1 Force and Moment in a Rotor; 2.2 Euler-Lagrange Approach; 2.3 Newton-Euler Approach.
505 8 $a 2.4 Quaternion Approach2.5 Discussion; References; Part 2 Improving Sensor Signals for Control Purposes; 3 Inertial Sensors Data Fusion for Orientation Estimation; 3.1 Attitude Representation; 3.2 Sensor Characterization; 3.3 Attitude Estimation Algorithms; 3.4 A Computationally-Efficient Kalman Filter; 3.5 Discussion; References; 4 Delay Signals & Predictors; 4.1 Observer-Predictor Algorithm for Compensation of Measurement Delays; 4.2 State Predictor-Control Scheme; 4.3 Discussion; References; 5 Data Fusion for UAV Localization; 5.1 Sensor Data Fusion.
505 8 $a 5.2 Prototype and Numerical Implementation5.3 Flight Tests and Experimental Results; 5.4 OptiTrack Measurements vs EKF Estimation; 5.5 Rotational Optical Flow Compensation; 5.6 Discussion; References; Part 3 Navigation Schemes & Control Strategies; 6 Nonlinear Control Algorithms with Integral Action; 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; 7 Sliding Mode Control; 7.1 From the Nonlinear Attitude Representation to Linear MIMO Expression.
505 8 $a 7.2 Nonlinear Optimal Controller with Integral Sliding Mode Design7.3 Numerical Validation; 7.4 Real-Time Validation; 7.5 Discussion; References; 8 Robust Simple Controllers; 8.1 Nonlinear Robust Algorithms Based on Saturation Functions; 8.2 Robust Control Based on an Uncertainty Estimator; 8.3 Discussion; References; 9 Trajectory Generation, Planning & Tracking; 9.1 Quadrotor Mathematical Description; 9.2 Time-Optimal Trajectory Generation; 9.3 UAV Routing Problem for Inspection-Like Missions; 9.4 Trajectory Tracking Problem; 9.5 Simulation Results; 9.6 Discussion; References.
505 8 $a 10 Obstacle Avoidance10.1 Artificial Potential Field Method; 10.2 Obstacle Avoidance Algorithm; 10.3 Limit-Cycle Obstacle Avoidance; 10.4 Discussion; References; 11 Haptic Teleoperation; 11.1 Experimental Setup; 11.2 Collision Avoidance; 11.3 Haptic Teleoperation; 11.4 Real-Time Experiments; 11.5 Discussion; References; Index; Back Cover.
520 $a 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 inautomatic control, mechatronics, robotics, and UAVs, helping them improve research and motivating them to build a test-bed for future projects.
650 0 $a Drone aircraft $x Control systems. $3 896751
650 0 $a Navigation (Aeronautics) $3 2134113
650 7 $a TECHNOLOGY & ENGINEERING $x Military Science. $2 bisacsh $3 1601150
655 0 $a Electronic books. $2 lcsh $3 542853
700 1 $a Muñoz Hernández, Laura Elena, $e author. $3 3509244
700 1 $a García Gil, Pedro, $e author. $3 3509245
856 4 0 $u https://www.sciencedirect.com/science/book/9780128051894