TY - CHAP
T1 - Principles of guidance, navigation, and control of uavs
AU - Elkaim, Gabriel Hugh
AU - Pradipta Lie, Fidelis Adhika
AU - Gebre-Egziabher, Demoz
N1 - Publisher Copyright:
© Springer Science+Business Media Dordrecht 2015.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Two complete system architectures for a guidance, navigation, and control solution of small UAVs are presented. These systems (developed at the University of California Santa Cruz and the University of Minnesota) are easily reconfigurable and are intended to support test beds used in navigation, guidance, and control research. The systems described both integrate a low-cost inertial measurement unit, a GPS receiver, and a triad of magnetometers to generate a navigation solution (position, velocity, and attitude estimation) which, in turn, is used in the guidance and control algorithms. The navigation solution described is a 15-state extendedKalman filter which integrates the inertial sensor and GPSmeasurement to generate a high-bandwidth estimate of a UAV’s state. Guidance algorithms for generating a flight trajectory based on waypoint definitions are also described. A PID controllerwhich uses the navigation filter estimate and guidance algorithm to track a flight trajectory is detailed. The full system architecture – the hardware, software, and algorithms – is included for completeness. Hardware in the loop simulation and flight test results documenting the performance of these two systems is given.
AB - Two complete system architectures for a guidance, navigation, and control solution of small UAVs are presented. These systems (developed at the University of California Santa Cruz and the University of Minnesota) are easily reconfigurable and are intended to support test beds used in navigation, guidance, and control research. The systems described both integrate a low-cost inertial measurement unit, a GPS receiver, and a triad of magnetometers to generate a navigation solution (position, velocity, and attitude estimation) which, in turn, is used in the guidance and control algorithms. The navigation solution described is a 15-state extendedKalman filter which integrates the inertial sensor and GPSmeasurement to generate a high-bandwidth estimate of a UAV’s state. Guidance algorithms for generating a flight trajectory based on waypoint definitions are also described. A PID controllerwhich uses the navigation filter estimate and guidance algorithm to track a flight trajectory is detailed. The full system architecture – the hardware, software, and algorithms – is included for completeness. Hardware in the loop simulation and flight test results documenting the performance of these two systems is given.
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U2 - 10.1007/978-90-481-9707-1_56
DO - 10.1007/978-90-481-9707-1_56
M3 - Chapter
AN - SCOPUS:84944563783
SN - 2014944662
SN - 9789048197064
SP - 347
EP - 380
BT - Handbook of Unmanned Aerial Vehicles
PB - Springer Netherlands
ER -